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Recent Advances in Model Predictive Control - Theory, Algorithms, and Applications (Hardcover, 1st ed. 2021)
Loot Price: R3,543
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Recent Advances in Model Predictive Control - Theory, Algorithms, and Applications (Hardcover, 1st ed. 2021)
Series: Lecture Notes in Control and Information Sciences, 485
Expected to ship within 10 - 15 working days
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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.
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