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Explicit Nonlinear Model Predictive Control Volume 429 by Grancharova, Alexandra; Johansen, Tor Arne is a scholarly article available to read on EtoBox.

What is Explicit Nonlinear Model Predictive Control Volume 429 about?

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: Ø Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; Ø Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs; Ø Nonlinear systems without uncertainty and nonlinear systems with uncert

Author

Grancharova, Alexandra; Johansen, Tor Arne

Publisher

Springer Berlin Heidelberg : Imprint: Springer

Published

2012

Language

EN

ISBN

9783642287794