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Recent advances in model predictive ...

Faulwasser, Timm.

Recent advances in model predictive controltheory, algorithms, and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recent advances in model predictive controledited by Timm Faulwasser, Matthias A. Muller, Karl Worthmann.
Reminder of title:	theory, algorithms, and applications /
other author:	Faulwasser, Timm.
Published:	Cham :Springer International Publishing :2021.
Description:	ix, 244 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Predictive control.
Online resource:	https://doi.org/10.1007/978-3-030-63281-6
ISBN:	9783030632816$q(electronic bk.)

Recent advances in model predictive controltheory, algorithms, and applications /
Recent advances in model predictive controltheory, algorithms, and applications /[electronic resource] :edited by Timm Faulwasser, Matthias A. Muller, Karl Worthmann. - Cham :Springer International Publishing :2021. - ix, 244 p. :ill. (some col.), digital ;24 cm. - Lecture notes in control and information sciences,v.4850170-8643 ;. - Lecture notes in control and information sciences ;315..

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.

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.

ISBN: 9783030632816$q(electronic bk.)

Standard No.: 10.1007/978-3-030-63281-6doiSubjects--Topical Terms:

182316
Predictive control.

LC Class. No.: TJ217.6 / .R434 2021

Dewey Class. No.: 629.8

Recent advances in model predictive controltheory, algorithms, and applications /
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505 0 $a 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.
520 $a 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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