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Controller and Optimization</title> <meta name="description" content="Search results for: PID Controller and Optimization"> <meta name="keywords" content="PID Controller and Optimization"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="PID Controller and Optimization"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3912</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: PID Controller and Optimization</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3912</span> Design of Optimal Proportional Integral Derivative Attitude Controller for an Uncoupled Flexible Satellite Using Particle Swarm Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martha%20C.%20Orazulume">Martha C. Orazulume</a>, <a href="https://publications.waset.org/abstracts/search?q=Jibril%20D.%20Jiya"> Jibril D. Jiya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Flexible satellites are equipped with various appendages which vibrate under the influence of any excitation and make the attitude of the satellite to be unstable. Therefore, the system must be able to adjust to balance the effect of these appendages in order to point accurately and satisfactorily which is one of the most important problems in satellite design. Proportional Integral Derivative (PID) Controller is simple to design and computationally efficient to implement which is used to stabilize the effect of these flexible appendages. However, manual turning of the PID is time consuming, waste energy and money. Particle Swarm Optimization (PSO) is used to tune the parameters of PID Controller. Simulation results obtained show that PSO tuned PID Controller is able to re-orient the spacecraft attitude as well as dampen the effect of mechanical resonance and yields better performance when compared with manually tuned PID Controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Attitude%20Control" title="Attitude Control">Attitude Control</a>, <a href="https://publications.waset.org/abstracts/search?q=Flexible%20Satellite" title=" Flexible Satellite"> Flexible Satellite</a>, <a href="https://publications.waset.org/abstracts/search?q=Particle%20Swarm%20Optimization" title=" Particle Swarm Optimization"> Particle Swarm Optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20Controller%20and%20Optimization" title=" PID Controller and Optimization"> PID Controller and Optimization</a> </p> <a href="https://publications.waset.org/abstracts/37412/design-of-optimal-proportional-integral-derivative-attitude-controller-for-an-uncoupled-flexible-satellite-using-particle-swarm-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37412.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">401</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3911</span> Tuning Fractional Order Proportional-Integral-Derivative Controller Using Hybrid Genetic Algorithm Particle Swarm and Differential Evolution Optimization Methods for Automatic Voltage Regulator System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fouzi%20Aboura">Fouzi Aboura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The fractional order proportional-integral-derivative (FOPID) controller or fractional order (PI位D碌) is a proportional-integral-derivative (PID) controller where integral order (位) and derivative order (碌) are fractional, one of the important application of classical PID is the Automatic Voltage Regulator (AVR).The FOPID controller needs five parameters optimization while the design of conventional PID controller needs only three parameters to be optimized. In our paper we have proposed a comparison between algorithms Differential Evolution (DE) and Hybrid Genetic Algorithm Particle Swarm Optimization (HGAPSO) ,we have studied theirs characteristics and performance analysis to find an optimum parameters of the FOPID controller, a new objective function is also proposed to take into account the relation between the performance criteria鈥檚. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FOPID%20controller" title="FOPID controller">FOPID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20order" title=" fractional order"> fractional order</a>, <a href="https://publications.waset.org/abstracts/search?q=AVR%20system" title=" AVR system"> AVR system</a>, <a href="https://publications.waset.org/abstracts/search?q=objective%20function" title=" objective function"> objective function</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=GA" title=" GA"> GA</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO" title=" PSO"> PSO</a>, <a href="https://publications.waset.org/abstracts/search?q=HGAPSO" title=" HGAPSO"> HGAPSO</a> </p> <a href="https://publications.waset.org/abstracts/164900/tuning-fractional-order-proportional-integral-derivative-controller-using-hybrid-genetic-algorithm-particle-swarm-and-differential-evolution-optimization-methods-for-automatic-voltage-regulator-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164900.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">90</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3910</span> Enhancing the Dynamic Performance of Grid-Tied Inverters Using Manta Ray Foraging Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20E.%20Keshta">H. E. Keshta</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20Ali"> A. A. Ali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Three phase grid-tied inverters are widely employed in micro-grids (MGs) as interphase between DC and AC systems. These inverters are usually controlled through standard decoupled d鈥搎 vector control strategy based on proportional integral (PI) controllers. Recently, advanced meta-heuristic optimization techniques have been used instead of deterministic methods to obtain optimum PI controller parameters. This paper provides a comparative study between the performance of the global Porcellio Scaber algorithm (GPSA) based PI controller and Manta Ray foraging optimization (MRFO) based PI controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=micro-grids" title="micro-grids">micro-grids</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20techniques" title=" optimization techniques"> optimization techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=grid-tied%20inverter%20control" title=" grid-tied inverter control"> grid-tied inverter control</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a> </p> <a href="https://publications.waset.org/abstracts/142353/enhancing-the-dynamic-performance-of-grid-tied-inverters-using-manta-ray-foraging-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142353.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3909</span> Optimization of Coefficients of Fractional Order Proportional-Integrator-Derivative Controller on Permanent Magnet Synchronous Motors Using Particle Swarm Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Motalebi%20Saraji">Ali Motalebi Saraji</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Zarei%20Lamuki"> Reza Zarei Lamuki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speed control and behavior improvement of permanent magnet synchronous motors (PMSM) that have reliable performance, low loss, and high power density, especially in industrial drives, are of great importance for researchers. Because of its importance in this paper, coefficients optimization of proportional-integrator-derivative fractional order controller is presented using Particle Swarm Optimization (PSO) algorithm in order to improve the behavior of PMSM in its speed control loop. This improvement is simulated in MATLAB software for the proposed optimized proportional-integrator-derivative fractional order controller with a Genetic algorithm and compared with a full order controller with a classic optimization method. Simulation results show the performance improvement of the proposed controller with respect to two other controllers in terms of rising time, overshoot, and settling time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speed%20control%20loop%20of%20permanent%20magnet%20synchronous%20motor" title="speed control loop of permanent magnet synchronous motor">speed control loop of permanent magnet synchronous motor</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20and%20full%20order%20proportional-integrator-derivative%20controller" title=" fractional and full order proportional-integrator-derivative controller"> fractional and full order proportional-integrator-derivative controller</a>, <a href="https://publications.waset.org/abstracts/search?q=coefficients%20optimization" title=" coefficients optimization"> coefficients optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=improvement%20of%20behavior" title=" improvement of behavior"> improvement of behavior</a> </p> <a href="https://publications.waset.org/abstracts/129038/optimization-of-coefficients-of-fractional-order-proportional-integrator-derivative-controller-on-permanent-magnet-synchronous-motors-using-particle-swarm-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129038.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3908</span> Improvement of the Robust Proportional鈥揑ntegral鈥揇erivative (PID) Controller Parameters for Controlling the Frequency in the Intelligent Multi-Zone System at the Present of Wind Generation Using the Seeker Optimization Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Roya%20Ahmadi%20Ahangar">Roya Ahmadi Ahangar</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Madadyari"> Hamid Madadyari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The seeker optimization algorithm (SOA) is increasingly gaining popularity among the researchers society due to its effectiveness in solving some real-world optimization problems. This paper provides the load-frequency control method based on the SOA for removing oscillations in the power system. A three-zone power system includes a thermal zone, a hydraulic zone and a wind zone equipped with robust proportional-integral-differential (PID) controllers. The result of simulation indicates that load-frequency changes in the wind zone for the multi-zone system are damped in a short period of time. Meanwhile, in the oscillation period, the oscillations amplitude is not significant. The result of simulation emphasizes that the PID controller designed using the seeker optimization algorithm has a robust function and a better performance for oscillations damping compared to the traditional PID controller. The proposed controller鈥檚 performance has been compared to the performance of PID controller regulated with Particle Swarm Optimization (PSO) and. Genetic Algorithm (GA) and Artificial Bee Colony (ABC) algorithms in order to show the superior capability of the proposed SOA in regulating the PID controller. The simulation results emphasize the better performance of the optimized PID controller based on SOA compared to the PID controller optimized with PSO, GA and ABC algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load-frequency%20control" title="load-frequency control">load-frequency control</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20zone" title=" multi zone"> multi zone</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20PID%20controller" title=" robust PID controller"> robust PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20generation" title=" wind generation"> wind generation</a> </p> <a href="https://publications.waset.org/abstracts/52309/improvement-of-the-robust-proportional-integral-derivative-pid-controller-parameters-for-controlling-the-frequency-in-the-intelligent-multi-zone-system-at-the-present-of-wind-generation-using-the-seeker-optimization-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52309.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">303</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3907</span> Parameters Tuning of a PID Controller on a DC Motor Using Honey Bee and Genetic Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeid%20Jalilzadeh">Saeid Jalilzadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=controller" title="controller">controller</a>, <a href="https://publications.waset.org/abstracts/search?q=GA" title=" GA"> GA</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=PID" title=" PID"> PID</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO" title=" PSO"> PSO</a> </p> <a href="https://publications.waset.org/abstracts/15526/parameters-tuning-of-a-pid-controller-on-a-dc-motor-using-honey-bee-and-genetic-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15526.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">544</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3906</span> An Efficient Design of Static Synchronous Series Compensator Based Fractional Order PID Controller Using Invasive Weed Optimization Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelghani%20Choucha">Abdelghani Choucha</a>, <a href="https://publications.waset.org/abstracts/search?q=Lakhdar%20Chaib"> Lakhdar Chaib</a>, <a href="https://publications.waset.org/abstracts/search?q=Salem%20Arif"> Salem Arif</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper treated the problem of power system stability with the aid of Static Synchronous Series Compensator (SSSC) installed in the transmission line of single machine infinite bus (SMIB) power system. A fractional order PID (FOPID) controller has been applied as a robust controller for optimal SSSC design to control the power system characteristics. Additionally, the SSSC based FOPID parameters are smoothly tuned using Invasive Weed Optimization algorithm (IWO). To verify the strength of the proposed controller, SSSC based FOPID controller is validated in a wide range of operating condition and compared with the conventional scheme SSSC-POD controller. The main purpose of the proposed process is greatly enhanced the dynamic states of the tested system. Simulation results clearly prove the superiority and performance of the proposed controller design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSSC-FOPID" title="SSSC-FOPID">SSSC-FOPID</a>, <a href="https://publications.waset.org/abstracts/search?q=SSSC-POD" title=" SSSC-POD"> SSSC-POD</a>, <a href="https://publications.waset.org/abstracts/search?q=SMIB%20power%20system" title=" SMIB power system"> SMIB power system</a>, <a href="https://publications.waset.org/abstracts/search?q=invasive%20weed%20optimization%20algorithm" title=" invasive weed optimization algorithm"> invasive weed optimization algorithm</a> </p> <a href="https://publications.waset.org/abstracts/78908/an-efficient-design-of-static-synchronous-series-compensator-based-fractional-order-pid-controller-using-invasive-weed-optimization-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78908.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3905</span> Control of Proton Exchange Membrane Fuel Cell Power System Using PI and Sliding Mode Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Derbeli">Mohamed Derbeli</a>, <a href="https://publications.waset.org/abstracts/search?q=Maissa%20Farhat"> Maissa Farhat</a>, <a href="https://publications.waset.org/abstracts/search?q=Oscar%20Barambones"> Oscar Barambones</a>, <a href="https://publications.waset.org/abstracts/search?q=Lassaad%20Sbita"> Lassaad Sbita</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conventional controller (PI) applied to a DC/DC boost converter for the improvement and optimization of the Proton Exchange Membrane Fuel Cell (PEMFC) system efficiency, cannot attain a good performance effect. Thus, due to its advantages comparatively with the PI controller, this paper interest is focused on the use of the sliding mode controller (SMC), Stability of the closed loop system is analytically proved using Lyapunov approach for the proposed controller. The model and the controllers are implemented in the MATLAB and SIMULINK environment. A comparison of results indicates that the suggested approach has considerable advantages compared to the traditional controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DC%2FDC%20boost%20converter" title="DC/DC boost converter">DC/DC boost converter</a>, <a href="https://publications.waset.org/abstracts/search?q=PEMFC" title=" PEMFC"> PEMFC</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=sliding%20mode%20controller" title=" sliding mode controller"> sliding mode controller</a> </p> <a href="https://publications.waset.org/abstracts/60160/control-of-proton-exchange-membrane-fuel-cell-power-system-using-pi-and-sliding-mode-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60160.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">234</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3904</span> A Comparative Study on a Tilt-Integral-Derivative Controller with Proportional-Integral-Derivative Controller for a Pacemaker</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aysan%20Esgandanian">Aysan Esgandanian</a>, <a href="https://publications.waset.org/abstracts/search?q=Sabalan%20Daneshvar"> Sabalan Daneshvar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study is done to determine the comparison between proportional-integral-derivative controller (PID controller) and tilt-integral-derivative (TID controller) for cardiac pacemaker systems, which can automatically control the heart rate to accurately track a desired preset profile. The controller offers good adaption of heart to the physiological needs of the patient. The parameters of the both controllers are tuned by particle swarm optimization (PSO) algorithm which uses the integral of time square error as a fitness function to be minimized. Simulation results are performed on the developed cardiovascular system of humans and results demonstrate that the TID controller produces superior control performance than PID controllers. In this paper, all simulations were performed in Matlab. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=integral%20of%20time%20square%20error" title="integral of time square error">integral of time square error</a>, <a href="https://publications.waset.org/abstracts/search?q=pacemaker%20systems" title=" pacemaker systems"> pacemaker systems</a>, <a href="https://publications.waset.org/abstracts/search?q=proportional-integral-derivative%20controller" title=" proportional-integral-derivative controller"> proportional-integral-derivative controller</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO%20algorithm" title=" PSO algorithm"> PSO algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=tilt-integral-derivative%20controller" title=" tilt-integral-derivative controller"> tilt-integral-derivative controller</a> </p> <a href="https://publications.waset.org/abstracts/43351/a-comparative-study-on-a-tilt-integral-derivative-controller-with-proportional-integral-derivative-controller-for-a-pacemaker" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43351.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">462</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3903</span> Direct Torque Control of Induction Motor Employing Teaching Learning Based Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anam%20Gopi">Anam Gopi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this Teaching Learning Based Optimization (TLBO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. The TLBO based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=teaching%20learning%20based%20optimization" title="teaching learning based optimization">teaching learning based optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20torque%20control" title=" direct torque control"> direct torque control</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a> </p> <a href="https://publications.waset.org/abstracts/31465/direct-torque-control-of-induction-motor-employing-teaching-learning-based-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31465.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">585</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3902</span> Optimal Tuning of Linear Quadratic Regulator Controller Using a Particle Swarm Optimization for Two-Rotor Aerodynamical System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ayad%20Al-Mahturi">Ayad Al-Mahturi</a>, <a href="https://publications.waset.org/abstracts/search?q=Herman%20Wahid"> Herman Wahid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=LQR%20controller" title="LQR controller">LQR controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization%20%28PSO%29" title=" particle swarm optimization (PSO)"> particle swarm optimization (PSO)</a>, <a href="https://publications.waset.org/abstracts/search?q=two%20rotor%20aero-dynamical%20system%20%28TRAS%29" title=" two rotor aero-dynamical system (TRAS)"> two rotor aero-dynamical system (TRAS)</a> </p> <a href="https://publications.waset.org/abstracts/65313/optimal-tuning-of-linear-quadratic-regulator-controller-using-a-particle-swarm-optimization-for-two-rotor-aerodynamical-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65313.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">323</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3901</span> Particle Swarm Optimization Based Vibration Suppression of a Piezoelectric Actuator Using Adaptive Fuzzy Sliding Mode Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jin-Siang%20Shaw">Jin-Siang Shaw</a>, <a href="https://publications.waset.org/abstracts/search?q=Patricia%20Moya%20Caceres"> Patricia Moya Caceres</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheng-Xiang%20Xu"> Sheng-Xiang Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to integrate the particle swarm optimization (PSO) method with the adaptive fuzzy sliding mode controller (AFSMC) to achieve vibration attenuation in a piezoelectric actuator subject to base excitation. The piezoelectric actuator is a complicated system made of ferroelectric materials and its performance can be affected by nonlinear hysteresis loop and unknown system parameters and external disturbances. In this study, an adaptive fuzzy sliding mode controller is proposed for the vibration control of the system, because the fuzzy sliding mode controller is designed to tackle the unknown parameters and external disturbance of the system, and the adaptive algorithm is aimed for fine-tuning this controller for error converging purpose. Particle swarm optimization method is used in order to find the optimal controller parameters for the piezoelectric actuator. PSO starts with a population of random possible solutions, called particles. The particles move through the search space with dynamically adjusted speed and direction that change according to their historical behavior, allowing the values of the particles to quickly converge towards the best solutions for the proposed problem. In this paper, an initial set of controller parameters is applied to the piezoelectric actuator which is subject to resonant base excitation with large amplitude vibration. The resulting vibration suppression is about 50%. Then PSO is applied to search for an optimal controller in the neighborhood of this initial controller. The performance of the optimal fuzzy sliding mode controller found by PSO indeed improves up to 97.8% vibration attenuation. Finally, adaptive version of fuzzy sliding mode controller is adopted for further improving vibration suppression. Simulation result verifies the performance of the adaptive controller with 99.98% vibration reduction. Namely the vibration of the piezoelectric actuator subject to resonant base excitation can be completely annihilated using this PSO based adaptive fuzzy sliding mode controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20sliding%20mode%20controller" title="adaptive fuzzy sliding mode controller">adaptive fuzzy sliding mode controller</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=piezoelectric%20actuator" title=" piezoelectric actuator"> piezoelectric actuator</a>, <a href="https://publications.waset.org/abstracts/search?q=vibration%20suppression" title=" vibration suppression"> vibration suppression</a> </p> <a href="https://publications.waset.org/abstracts/99760/particle-swarm-optimization-based-vibration-suppression-of-a-piezoelectric-actuator-using-adaptive-fuzzy-sliding-mode-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99760.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3900</span> Desing of PSS and SVC to Improve Power System Stability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20Samkan">Mahmoud Samkan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the design and assessment of new coordination between Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method are proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SVC" title="SVC">SVC</a>, <a href="https://publications.waset.org/abstracts/search?q=PSSs" title=" PSSs"> PSSs</a>, <a href="https://publications.waset.org/abstracts/search?q=multimachine%20power%20system" title=" multimachine power system"> multimachine power system</a>, <a href="https://publications.waset.org/abstracts/search?q=coordinated%20design" title=" coordinated design"> coordinated design</a>, <a href="https://publications.waset.org/abstracts/search?q=bacteria%20swarm%20optimization" title=" bacteria swarm optimization"> bacteria swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20assessment" title=" statistical assessment "> statistical assessment </a> </p> <a href="https://publications.waset.org/abstracts/36661/desing-of-pss-and-svc-to-improve-power-system-stability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36661.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3899</span> Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Gherbi">S. Gherbi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Bouchareb"> F. Bouchareb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=delayed%20systems" title="delayed systems">delayed systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20immune%20PID" title=" fuzzy immune PID"> fuzzy immune PID</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Smith%20predictor" title=" Smith predictor"> Smith predictor</a> </p> <a href="https://publications.waset.org/abstracts/10235/optimal-tuning-of-a-fuzzy-immune-pid-parameters-to-control-a-delayed-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10235.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">433</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3898</span> Speed Control of DC Motor Using Optimization Techniques Based PID Controller </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Santosh%20Kumar%20Suman">Santosh Kumar Suman</a>, <a href="https://publications.waset.org/abstracts/search?q=Vinod%20Kumar%20Giri"> Vinod Kumar Giri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DC%20motor" title="DC motor">DC motor</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20controller" title=" PID controller"> PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20techniques" title=" optimization techniques"> optimization techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm%20%28GA%29" title=" genetic algorithm (GA)"> genetic algorithm (GA)</a>, <a href="https://publications.waset.org/abstracts/search?q=objective%20function" title=" objective function"> objective function</a>, <a href="https://publications.waset.org/abstracts/search?q=IAE" title=" IAE"> IAE</a> </p> <a href="https://publications.waset.org/abstracts/48103/speed-control-of-dc-motor-using-optimization-techniques-based-pid-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48103.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">420</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3897</span> Model-Based Control for Piezoelectric-Actuated Systems Using Inverse Prandtl-Ishlinskii Model and Particle Swarm Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jin-Wei%20Liang">Jin-Wei Liang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hung-Yi%20Chen"> Hung-Yi Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Lung%20Lin"> Lung Lin </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=the%20Bouc-Wen%20hysteresis%20model" title="the Bouc-Wen hysteresis model">the Bouc-Wen hysteresis model</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Prandtl-Ishlinskii%20model" title=" Prandtl-Ishlinskii model"> Prandtl-Ishlinskii model</a>, <a href="https://publications.waset.org/abstracts/search?q=automation%20engineering" title=" automation engineering"> automation engineering</a> </p> <a href="https://publications.waset.org/abstracts/4325/model-based-control-for-piezoelectric-actuated-systems-using-inverse-prandtl-ishlinskii-model-and-particle-swarm-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4325.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">514</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3896</span> Parallel Particle Swarm Optimization Optimized LDI Controller with Lyapunov Stability Criterion for Nonlinear Structural Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20W.%20Tsai">P. W. Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20L.%20Hong"> W. L. Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20W.%20Chen"> C. W. Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Y.%20Chen"> C. Y. Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lyapunov%20stability" title="Lyapunov stability">Lyapunov stability</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20particle%20swarm%20optimization" title=" parallel particle swarm optimization"> parallel particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20differential%20inclusion" title=" linear differential inclusion"> linear differential inclusion</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a> </p> <a href="https://publications.waset.org/abstracts/6974/parallel-particle-swarm-optimization-optimized-ldi-controller-with-lyapunov-stability-criterion-for-nonlinear-structural-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6974.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">656</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3895</span> Optimal Tuning of RST Controller Using PSO Optimization for Synchronous Generator Based Wind Turbine under Three-Phase Voltage Dips</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Tahir">K. Tahir</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Belfedal"> C. Belfedal</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Allaoui"> T. Allaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Gerard"> C. Gerard</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Doumi"> M. Doumi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we presented an optimized RST controller using Particle Swarm Optimization (PSO) meta-heuristic technique of the active and reactive power regulation of a grid connected wind turbine based on a wound field synchronous generator. This regulation is achieved below the synchronous speed, by means of a maximum power point tracking algorithm. The control of our system is tested under typical wind variations and parameters variation, fault grid condition by simulation. Some results are presented and discussed to prove simplicity and efficiency of the WRSG control for WECS. On the other hand, according to simulation results, variable speed driven WRSG is not significantly impacted in fault conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20energy" title="wind energy">wind energy</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=wound%20rotor%20synchronous%20generator" title=" wound rotor synchronous generator"> wound rotor synchronous generator</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20control" title=" power control"> power control</a>, <a href="https://publications.waset.org/abstracts/search?q=RST%20controller" title=" RST controller"> RST controller</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20power%20point%20tracking" title=" maximum power point tracking"> maximum power point tracking</a> </p> <a href="https://publications.waset.org/abstracts/12646/optimal-tuning-of-rst-controller-using-pso-optimization-for-synchronous-generator-based-wind-turbine-under-three-phase-voltage-dips" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12646.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">451</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3894</span> Design and Simulation of Unified Power Quality Conditioner based on Adaptive Fuzzy PI Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Brahim%20Ferdi">Brahim Ferdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Samira%20Dib"> Samira Dib</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The unified power quality conditioner (UPQC), a combination of shunt and series active power filter, is one of the best solutions towards the mitigation of voltage and current harmonics problems in distribution power system. PI controller is very common in the control of UPQC. However, one disadvantage of this conventional controller is the difficulty in tuning its gains (Kp and Ki). To overcome this problem, an adaptive fuzzy logic PI controller is proposed. The controller is composed of fuzzy controller and PI controller. According to the error and error rate of the control system and fuzzy control rules, the fuzzy controller can online adjust the two gains of the PI controller to get better performance of UPQC. Simulations using MATLAB/SIMULINK are carried out to verify the performance of the proposed controller. The results show that the proposed controller has fast dynamic response and high accuracy of tracking the current and voltage references. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20PI%20controller" title="adaptive fuzzy PI controller">adaptive fuzzy PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=current%20harmonics" title=" current harmonics"> current harmonics</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=voltage%20harmonics" title=" voltage harmonics"> voltage harmonics</a>, <a href="https://publications.waset.org/abstracts/search?q=UPQC" title=" UPQC"> UPQC</a> </p> <a href="https://publications.waset.org/abstracts/16996/design-and-simulation-of-unified-power-quality-conditioner-based-on-adaptive-fuzzy-pi-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16996.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">556</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3893</span> Robotic Arm Control with Neural Networks Using Genetic Algorithm Optimization Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arbnor%20Pajaziti">Arbnor Pajaziti</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20Cana"> Hasan Cana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=robotic%20arm" title="robotic arm">robotic arm</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/7408/robotic-arm-control-with-neural-networks-using-genetic-algorithm-optimization-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7408.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">523</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3892</span> Optimization of the Control Scheme for Human Extremity Exoskeleton</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang%20Li">Yang Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaorong%20Guan"> Xiaorong Guan</a>, <a href="https://publications.waset.org/abstracts/search?q=Cheng%20Xu"> Cheng Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to design a suitable control scheme for human extremity exoskeleton, the interaction force control scheme with traditional PI controller was presented, and the simulation study of the electromechanical system of the human extremity exoskeleton was carried out by using a MATLAB/Simulink module. By analyzing the simulation calculation results, it was shown that the traditional PI controller is not very suitable for every movement speed of human body. So, at last the fuzzy self-adaptive PI controller was presented to solve this problem. Eventually, the superiority and feasibility of the fuzzy self-adaptive PI controller was proved by the simulation results and experimental results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=human%20extremity%20exoskeleton" title="human extremity exoskeleton">human extremity exoskeleton</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20force%20control%20scheme" title=" interaction force control scheme"> interaction force control scheme</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation%20study" title=" simulation study"> simulation study</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20self-adaptive%20pi%20controller" title=" fuzzy self-adaptive pi controller"> fuzzy self-adaptive pi controller</a>, <a href="https://publications.waset.org/abstracts/search?q=man-machine%20coordinated%20walking" title=" man-machine coordinated walking"> man-machine coordinated walking</a>, <a href="https://publications.waset.org/abstracts/search?q=bear%20payload" title=" bear payload"> bear payload</a> </p> <a href="https://publications.waset.org/abstracts/53441/optimization-of-the-control-scheme-for-human-extremity-exoskeleton" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53441.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">362</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3891</span> Maximum Power Point Tracking Using Fuzzy Logic Control for a Stand-Alone PV System with PI Controller for Battery Charging Based on Evolutionary Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20A.%20Moustafa%20Hassan">Mohamed A. Moustafa Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Omnia%20S%20.S.%20Hussian"> Omnia S .S. Hussian</a>, <a href="https://publications.waset.org/abstracts/search?q=Hany%20M.%20Elsaved"> Hany M. Elsaved</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces the application of Fuzzy Logic Controller (FLC) to extract the Maximum Power Point Tracking (MPPT) from the PV panel. In addition, the proportional integral (PI) controller is used to be the strategy for battery charge control according to acceptable performance criteria. The parameters of the PI controller have been tuned via Modified Adaptive Accelerated Coefficient Particle Swarm Optimization (MAACPSO) technique. The simulation results, using MATLAB/Simulink tools, show that the FLC technique has advantages for use in the MPPT problem, as it provides a fast response under changes in environmental conditions such as radiation and temperature. In addition, the use of PI controller based on MAACPSO results in a good performance in terms of controlling battery charging with constant voltage and current to execute rapid charging. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=battery%20charging" title="battery charging">battery charging</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20control" title=" fuzzy logic control"> fuzzy logic control</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20power%20point%20tracking" title=" maximum power point tracking"> maximum power point tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=PV%20system" title=" PV system"> PV system</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20technique" title=" evolutionary technique"> evolutionary technique</a> </p> <a href="https://publications.waset.org/abstracts/109686/maximum-power-point-tracking-using-fuzzy-logic-control-for-a-stand-alone-pv-system-with-pi-controller-for-battery-charging-based-on-evolutionary-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109686.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">166</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3890</span> Optimal Driving Strategies for a Hybrid Street Type Motorcycle: Modelling and Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jhon%20Vargas">Jhon Vargas</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilberto%20Osorio-Gomez"> Gilberto Osorio-Gomez</a>, <a href="https://publications.waset.org/abstracts/search?q=Tatiana%20Manrique"> Tatiana Manrique</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20model" title="dynamic model">dynamic model</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20strategies" title=" driving strategies"> driving strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20hybrid%20motorcycle" title=" parallel hybrid motorcycle"> parallel hybrid motorcycle</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20controller" title=" PID controller"> PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/133692/optimal-driving-strategies-for-a-hybrid-street-type-motorcycle-modelling-and-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133692.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">189</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3889</span> A Robust PID Load Frequency Controller of Interconnected Power System Using SDO Software</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pasala%20Gopi">Pasala Gopi</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Linga%20Reddy"> P. Linga Reddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The response of the load frequency control problem in an multi-area interconnected electrical power system is much more complex with increasing size, changing structure and increasing load. This paper deals with Load Frequency Control of three area interconnected Power system incorporating Reheat, Non-reheat and Reheat turbines in all areas respectively. The response of the load frequency control problem in an multi-area interconnected power system is improved by designing PID controller using different tuning techniques and proved that the PID controller which was designed by Simulink Design Optimization (SDO) Software gives the superior performance than other controllers for step perturbations. Finally the robustness of controller was checked against system parameter variations <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load%20frequency%20control" title="load frequency control">load frequency control</a>, <a href="https://publications.waset.org/abstracts/search?q=pid%20controller%20tuning" title=" pid controller tuning"> pid controller tuning</a>, <a href="https://publications.waset.org/abstracts/search?q=step%20load%20perturbations" title=" step load perturbations"> step load perturbations</a>, <a href="https://publications.waset.org/abstracts/search?q=inter%20connected%20power%20system" title=" inter connected power system"> inter connected power system</a> </p> <a href="https://publications.waset.org/abstracts/30053/a-robust-pid-load-frequency-controller-of-interconnected-power-system-using-sdo-software" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30053.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">644</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3888</span> Designing Intelligent Adaptive Controller for Nonlinear Pendulum Dynamical System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Ghasemi">R. Ghasemi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Rahimi%20Khoygani"> M. R. Rahimi Khoygani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20neural%20controller" title="adaptive neural controller">adaptive neural controller</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20dynamical" title=" nonlinear dynamical"> nonlinear dynamical</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=RBF" title=" RBF"> RBF</a>, <a href="https://publications.waset.org/abstracts/search?q=driven%20pendulum" title=" driven pendulum"> driven pendulum</a>, <a href="https://publications.waset.org/abstracts/search?q=position%20control" title=" position control "> position control </a> </p> <a href="https://publications.waset.org/abstracts/13745/designing-intelligent-adaptive-controller-for-nonlinear-pendulum-dynamical-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13745.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">482</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3887</span> A Single Loop Repetitive Controller for a Four Legs Matrix Converter Unit</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wesam%20Rohouma">Wesam Rohouma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to investigate the use of repetitive controller to regulate the output voltage of three phase four leg matric converter for an Aircraft Ground Power Supply Unit. The proposed controller improve the steady state error and provide good regulation during different loading. Simulation results of 7.5 KW converter are presented to verify the operation of the proposed controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=matrix%20converter" title="matrix converter">matrix converter</a>, <a href="https://publications.waset.org/abstracts/search?q=Power%20electronics" title=" Power electronics"> Power electronics</a>, <a href="https://publications.waset.org/abstracts/search?q=controller" title=" controller"> controller</a>, <a href="https://publications.waset.org/abstracts/search?q=regulation" title=" regulation"> regulation</a> </p> <a href="https://publications.waset.org/abstracts/18181/a-single-loop-repetitive-controller-for-a-four-legs-matrix-converter-unit" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18181.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1506</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3886</span> Optimization Techniques of Doubly-Fed Induction Generator Controller Design for Reliability Enhancement of Wind Energy Conversion Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Om%20Prakash%20Bharti">Om Prakash Bharti</a>, <a href="https://publications.waset.org/abstracts/search?q=Aanchal%20Verma"> Aanchal Verma</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20K.%20Saket"> R. K. Saket</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=doubly-fed%20induction%20generator" title="doubly-fed induction generator">doubly-fed induction generator</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine" title=" wind turbine"> wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy%20conversion%20system" title=" wind energy conversion system"> wind energy conversion system</a>, <a href="https://publications.waset.org/abstracts/search?q=induction%20generator" title=" induction generator"> induction generator</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer%20function" title=" transfer function"> transfer function</a>, <a href="https://publications.waset.org/abstracts/search?q=proportional" title=" proportional"> proportional</a>, <a href="https://publications.waset.org/abstracts/search?q=integral" title=" integral"> integral</a>, <a href="https://publications.waset.org/abstracts/search?q=derivatives" title=" derivatives"> derivatives</a> </p> <a href="https://publications.waset.org/abstracts/157706/optimization-techniques-of-doubly-fed-induction-generator-controller-design-for-reliability-enhancement-of-wind-energy-conversion-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157706.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">93</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3885</span> Designing Back-Stepping Sliding Mode Controller for a Class of 4Y Octorotor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=I.%20Khabbazi">I. Khabbazi</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Ghasemi"> R. Ghasemi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a combination of both robust nonlinear controller and nonlinear controller for a class of nonlinear 4Y Octorotor UAV using Back-stepping and sliding mode controller. The robustness against internal and external disturbance and decoupling control are the merits of the proposed paper. The proposed controller decouples the Octorotor dynamical system. The controller is then applied to a 4Y Octorotor UAV and its feature will be shown. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sliding%20mode" title="sliding mode">sliding mode</a>, <a href="https://publications.waset.org/abstracts/search?q=backstepping" title=" backstepping"> backstepping</a>, <a href="https://publications.waset.org/abstracts/search?q=decoupling" title=" decoupling"> decoupling</a>, <a href="https://publications.waset.org/abstracts/search?q=octorotor%20UAV" title=" octorotor UAV"> octorotor UAV</a> </p> <a href="https://publications.waset.org/abstracts/14595/designing-back-stepping-sliding-mode-controller-for-a-class-of-4y-octorotor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14595.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">440</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3884</span> Hybrid GA-PSO Based Pitch Controller Design for Aircraft Control System </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vaibhav%20Singh%20%20Rajput">Vaibhav Singh Rajput</a>, <a href="https://publications.waset.org/abstracts/search?q=Ravi%20Kumar%20Jatoth"> Ravi Kumar Jatoth</a>, <a href="https://publications.waset.org/abstracts/search?q=Nagu%20Bhookya"> Nagu Bhookya</a>, <a href="https://publications.waset.org/abstracts/search?q=Bhasker%20Boda"> Bhasker Boda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper proportional, integral, derivative (PID) controller is used to control the pitch angle of the aircraft when the elevation angle is changed or modified. The pitch angle is dependent on elevation angle; a change in one corresponds to a change in the other. The PID controller helps in restricted change of pitch rate in response to the elevation angle. The PID controller is dependent on different parameters like Kp, Ki, Kd which change the pitch rate as they change. Various methodologies are used for changing those parameters for getting a perfect time response pitch angle, as desired or wished by a concerned person. While reckoning the values of those parameters, trial and guessing may prove to be futile in order to provide comfort to passengers. So, using some metaheuristic techniques can be useful in handling these errors. Hybrid GA-PSO is one such powerful algorithm which can improve transient and steady state response and can give us more reliable results for PID gain scheduling problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pitch%20rate" title="pitch rate">pitch rate</a>, <a href="https://publications.waset.org/abstracts/search?q=elevation%20angle" title=" elevation angle"> elevation angle</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20controller" title=" PID controller"> PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=phugoid" title=" phugoid"> phugoid</a> </p> <a href="https://publications.waset.org/abstracts/64457/hybrid-ga-pso-based-pitch-controller-design-for-aircraft-control-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">328</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3883</span> Intelligent Path Tracking Hybrid Fuzzy Controller for a Unicycle-Type Differential Drive Robot</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20M.%20Almeshal">Abdullah M. Almeshal</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20R.%20Alenezi"> Mohammad R. Alenezi</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Moaz"> Muhammad Moaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=differential%20drive%20robot" title="differential drive robot">differential drive robot</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20fuzzy%20controller" title=" hybrid fuzzy controller"> hybrid fuzzy controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20tracking" title=" path tracking"> path tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=unicycle%20robot" title=" unicycle robot"> unicycle robot</a> </p> <a href="https://publications.waset.org/abstracts/30098/intelligent-path-tracking-hybrid-fuzzy-controller-for-a-unicycle-type-differential-drive-robot" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30098.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">463</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=PID%20Controller%20and%20Optimization&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=PID%20Controller%20and%20Optimization&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=PID%20Controller%20and%20Optimization&page=4">4</a></li> <li class="page-item"><a class="page-link" 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