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Optimal Control Applications and Methods

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Optimal Control Applications and Methods will provide a forum for papers on the full range of optimal control and related control design methods. The aim is to encourage new developments in optimal control theory and design methodologies that may lead to advances in real control applications. Papers are encouraged on the development of computational algorithms for solving optimal control and optimization problems. The scope includes papers on optimal estimation and filtering methods that have control-related applications. It will also provide a venue for interesting optimal control applications and design studies. Papers on linear and nonlinear predictive control methods will be particularly encouraged. Suitable papers will normally be concerned with model based optimal control methods covering topics such as optimal control in multi-agent systems, optimal nonlinear and robust control, H2 and H∞ design, linear-quadratic control, stochastic control, multi-criteria and multiple-model control. It also covers optimal control of hybrid systems, switching systems, repetitive and periodic control. The optimal adaptive control of systems is of interest and large-scale systems, distributed systems and time-delay systems. Optimal estimation and filtering methods are included, and optimal fault estimation, safety-critical, fault-tolerant and reliable control systems. Topics in optimization algorithms for control are relevant such as static and dynamic optimization techniques, nonlinear programming, constrained control and dynamic programming. There is a strong interest in engineering applications including: manufacturing and industrial processes, aerospace and defence, marine and automotive systems, electro-mechanical systems, robotics, electrical power generation and distribution systems, energy systems (including wind turbines, wave, tidal, battery, fuel cell, solar, and refining systems), chemical and petrochemical processes, biological and biomedical systems, environmental control, water treatment and distribution, electrical and electronic systems, networked control, and control of networks. Applications of interest also include a wide range of interdisciplinary, decentralized, complex systems, where multi-agent solutions, artificial intelligence, intelligent sensors, cyber physical systems, and either static or dynamic optimization play a role. Readership Control system, electrical, mechanical, process, systems and instrumentation engineers, and scientists and applied mathematicians. Keywords Optimal control, predictive control, process optimization, robust control, uncertain systems, stochastic systems, optimization methods, nonlinear optimal control, optimal adaptive control, dynamic programming, discrete-time systems, hybrid systems, optimal control applications, optimal filtering and estimation.</pre><div class="alert alert-warning"> Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-08-20</div> </div> </div> <!-- <div class="hidden-phone"> <div align="center"> <table border="0" align="center" cellpadding="0" cellspacing="1" class="noScroll"> <tr> <td width="180"><div align="center"> <a target="_blank" href=""><img src="" alt="" border="0" style="width:110;height:160" title=""/></a> <br /> <br /> </div></td> </tr> <tr> </tr> </table> <div align="center"><a target="_blank" href=""> >></a></div> </div> </div> --> <div class="portlet" id="yw3"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-file"></i> Related 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