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This book nds its origin in the WIDE PhD School on Networked
Control Systems, which we organized in July 2009 in Siena, Italy.
Having gathered experts on all the aspects of networked control
systems, it was a small step to go from the summer school to the
book, certainly given the enthusiasm of the lecturers at the
school. We felt that a book collecting overviewson the important
developmentsand open pr- lems in the eld of networked control
systems could stimulate and support future research in this
appealing area. Given the tremendouscurrentinterests in distributed
control exploiting wired and wireless communication networks, the
time seemed to be right for the book that lies now in front of you.
The goal of the book is to set out the core techniques and tools
that are ava- able for the modeling, analysis and design of
networked control systems. Roughly speaking, the book consists of
three parts. The rst part presents architectures for distributed
control systems and models of wired and wireless communication n-
works. In particular, in the rst chapter important technological
and architectural aspects on distributed control systems are
discussed. The second chapter provides insight in the behavior of
communication channels in terms of delays, packet loss and
information constraints leading to suitable modeling paradigms for
commu- cation networks.
Model Predictive Control (MPC), the dominant advanced control
approach in industry over the past twenty-five years, is presented
comprehensively in this unique book. With a simple, unified
approach, and with attention to real-time implementation, it covers
predictive control theory including the stability, feasibility, and
robustness of MPC controllers. The theory of explicit MPC, where
the nonlinear optimal feedback controller can be calculated
efficiently, is presented in the context of linear systems with
linear constraints, switched linear systems, and, more generally,
linear hybrid systems. Drawing upon years of practical experience
and using numerous examples and illustrative applications, the
authors discuss the techniques required to design predictive
control laws, including algorithms for polyhedral manipulations,
mathematical and multiparametric programming and how to validate
the theoretical properties and to implement predictive control
policies. The most important algorithms feature in an accompanying
free online MATLAB toolbox, which allows easy access to sample
solutions. Predictive Control for Linear and Hybrid Systems is an
ideal reference for graduate, postgraduate and advanced control
practitioners interested in theory and/or implementation aspects of
predictive control.
Model Predictive Control (MPC), the dominant advanced control
approach in industry over the past twenty-five years, is presented
comprehensively in this unique book. With a simple, unified
approach, and with attention to real-time implementation, it covers
predictive control theory including the stability, feasibility, and
robustness of MPC controllers. The theory of explicit MPC, where
the nonlinear optimal feedback controller can be calculated
efficiently, is presented in the context of linear systems with
linear constraints, switched linear systems, and, more generally,
linear hybrid systems. Drawing upon years of practical experience
and using numerous examples and illustrative applications, the
authors discuss the techniques required to design predictive
control laws, including algorithms for polyhedral manipulations,
mathematical and multiparametric programming and how to validate
the theoretical properties and to implement predictive control
policies. The most important algorithms feature in an accompanying
free online MATLAB toolbox, which allows easy access to sample
solutions. Predictive Control for Linear and Hybrid Systems is an
ideal reference for graduate, postgraduate and advanced control
practitioners interested in theory and/or implementation aspects of
predictive control.
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Discovery Miles 3 300
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