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Author Grancharova, Alexandra.

Title Explicit nonlinear model predictive control : theory and applications / Alexandra Grancharova and Tor Arne Johansen
Published Berlin ; New York : Springer, [2012]
©2012
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Description 1 online resource (xiv, 234 pages)
Series Lecture notes in control and information sciences, 0170-8643 ; 429
Lecture notes in control and information sciences ; 429
Contents Multi-parametric Programming -- Nonlinear Model Predictive Control -- Explicit NMPC Using mp-QP Approximations of mp-NLP -- Explicit NMPC via Approximate mp-NLP -- Explicit MPC of Constrained Nonlinear Systems with Quantized Inputs -- Explicit Min-Max MPC of Constrained Nonlinear Systems with Bounded Uncertainties -- Explicit Stochastic NMPC -- Explicit NMPC Based on Neural Network Models -- Semi-explicit Distributed NMPC
Summary Annotation Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Nonlinear systems described by first-principles models and nonlinear systems described by black-box models;- Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs;- Nonlinear systems without uncertainty and nonlinear systems with uncertainties (polyhedral description of uncertainty and stochastic description of uncertainty);- Nonlinear systems, consisting of interconnected nonlinear sub-systems. The proposed mp-NLP approaches are illustrated with applications to several case studies, which are taken from diverse areas such as automotive mechatronics, compressor control, combustion plant control, reactor control, pH maintaining system control, cart and spring system control, and diving computers
Analysis Engineering
Systems theory
Control
Complexity
Systems Theory, Control
Nonlinear Dynamics
Bibliography Includes bibliographical references and index
Subject Predictive control.
Nonlinear control theory.
Form Electronic book
Author Johansen, Tor Arne.
ISBN 3642287794 (isbn gedrukte versie)
3642287808 (electronic bk.)
9783642287794 (isbn gedrukte versie)
9783642287800 (electronic bk.)