The stability of equilibrium points plays a fundamental role in dynamical systems. For nonlinear dynamical systems, which represent the majority of real plants, an investigation of stability requires the characterization of the domain of attraction (DA) of an equilibrium point, i.e., the set of initial conditions from which the trajectory of the system converges to such a point. It is well-known that estimating the DA, or even more attempting to control it, are very difficult problems because of the complex relationship of this set with the model of the system.

The book also offers a concise and simple description of the main features of SOS programming which can be used in research and teaching. In particular, it introduces various classes of SOS polynomials and their characterization via LMIs and addresses typical problems such as establishment of positivity or non-positivity of polynomials and matrix polynomials, determining the minimum of rational functions, and solving systems of polynomial equations, in cases of both unconstrained and constrained variables. The techniques presented in this book are available in the MATLAB® toolbox SMRSOFT, which can be downloaded from http://www.eee.hku.hk/~chesi.

Domain of Attraction addresses the estimation and control of the DA of equilibrium points using the novel SOS programming scheme, i.e., optimization techniques that have been recently developed based on polynomials that are sums of squares of polynomials (SOS polynomials) and that amount to solving convex optimization problems with linear matrix inequality (LMI)constraints, also known as semidefinite programs (SDPs). For the first time in the literature, a means of dealing with these issues is presented in a unified framework for various cases depending on the nature of the nonlinear systems considered, including the cases of polynomial systems, uncertain polynomial systems, and nonlinear (possibly uncertain) non-polynomial systems. The methods proposed in this book are illustrated in a variety of real systems and simulated systems with randomly chosen structures and/or coefficients which includes chemical reactors, electric circuits, mechanical devices, and social models.

Autorentext

Graziano Chesi received the Laurea degree in Information Engineering from the University of Firenze (Italy) in 1997, and the Ph.D. in Systems Engineering from the University of Bologna (Italy) in 2001. He was a visiting scientist at the Department of Engineering of the University of Cambridge (UK) in the period 1999-2000. He held fellowships from the Japanese Society for the Promotion of Science and the European Union at the Department of Information Physics and Computing of the University of Tokyo (Japan) in the period 2001-2004. He was a Research Associate and an Assistant Professor at the Department of Information Engineering of the University of Siena (Italy) in the period 2000-2006. In 2006 he joined the Department of Electrical and Electronic Engineering of the University of Hong Kong (Hong Kong). Dr. Chesi was the recipient of the Best Student Award of the Faculty of Engineering of the University of Firenze in 1997. He is an Associate Editor of Automatica, an Associate Editor of the IEEE Transactions on Automatic Control, and a Guest Editor of the Special Issue of the IEEE Transactions on Automatic Control on "Positive Polynomials in Control". His research interests include computer vision, nonlinear systems, optimization, robotics, robust control, and systems biology.

Klappentext

For nonlinear dynamical systems, which represent the majority of real devices, any study of stability requires the investigation of the domain of attraction of an equilibrium point, i.e. the set of initial conditions from which the trajectory of the system converges to equilibrium. Unfortunately, both estimating and attempting to control the domain of attraction are very difficult problems, because of the complex relationship of this set with the model of the system. Domain of Attraction addresses the estimation and control of the domain of attraction of equilibrium points via SOS programming, i.e. optimization techniques based on the sum of squares of polynomials (SOS) that have been recently developed and that amount to solving convex problems with linear matrix inequality constraints. A unified framework for addressing these issues is presented for in various cases depending on the nature of the nonlinear systems considered, including the cases of polynomial, non-polynomial, certain and uncertain systems. The methods proposed are illustrated various example systems such as electric circuits, mechanical devices, and nuclear plants. Domain of Attraction also deals with related problems that can be considered within the proposed framework, such as characterizing the equilibrium points and bounding the trajectories of nonlinear systems, and offers a concise and simple description of the main features of SOS programming, which can be used for general purpose in research and teaching.

Inhalt

SOS Polynomials.- Optimization with SOS Polynomials.- Preliminaries of Nonlinear Systems.- Domain of Attraction in Polynomial Systems.- Domain of Attraction in Uncertain Polynomial Systems.- Domain of Attraction in Non-polynomial Systems.- Domain of Attraction via Multiple Lyapunov Function.- Miscellaneous.