Recent Advances in Model Predictive Control: Theory, Algorithms, and Application

Description: Recent Advances in Model Predictive Control by Timm Faulwasser, Karl Worthmann, Matthias A. MÜller Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role.The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role.The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders. Back Cover This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders. Table of Contents Predictive path-following without terminal constraints.- Dissipativity in economic model predictive control: beyond steady-state optimality.- Primal or dual terminal constraints in Economic MPC? –s Comparison and insights.- Multi-level iterations for economic nonlinear model predictive control.- On closed-loop dynamics of ADMM-based MPC.- Distributed optimization and control with ALADIN.- Model predictive control for the internet of things.- Hybrid GP modeling applied to economic stochastic MPC of batch processes.- Collision avoidance for mobile robots based on an occupancy grid. Feature Presents some recent advances in the field of model predictive control (MPC), in particular economic MPC, distributed MPC, and applications thereof in different areas Exhibits a number of challenging questions both for theoretical developments and for practical implementation issues Is of interest to a large audience in the field of systems and control Details ISBN3030632830 Short Title Recent Advances in Model Predictive Control Pages 244 Series Lecture Notes in Control and Information Sciences Language English Year 2022 ISBN-10 3030632830 ISBN-13 9783030632830 Format Paperback Subtitle Theory, Algorithms, and Applications Series Number 485 Publisher Springer Nature Switzerland AG Edition 1st Imprint Springer Nature Switzerland AG Place of Publication Cham Country of Publication Switzerland Publication Date 2022-04-18 Illustrations 41 Illustrations, color; 12 Illustrations, black and white; IX, 244 p. 53 illus., 41 illus. in color. UK Release Date 2022-04-18 Author Matthias A. MÜller Edited by Matthias A. MÜller Edition Description 1st ed. 2021 Alternative 9783030632809 DEWEY 515.642 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:135089944;

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