Analysis and Design of Singular Markovian Jump Systems

This monograph is an up-to-date presentation of the analysis and design of singular Markovian jump systems (SMJSs) in which the transition rate matrix of the underlying systems is generally uncertain, partially unknown and designed. The problems addressed include stability, stabilization, H control and filtering, observer design, and adaptive control. applications of Markov process are investigated by using Lyapunov theory, linear matrix inequalities (LMIs), S-procedure and the stochastic Barbalat's Lemma, among other techniques.

Features of the book include:

· study of the stability problem for SMJSs with general transition rate matrices (TRMs);

· stabilization for SMJSs by TRM design, noise control, proportional-derivative and partially mode-dependent control, in terms of LMIs with and without equation constraints;

· mode-dependent and mode-independent H control solutions with development of a type of disordered controller;

· observer-based controllers of SMJSs in which both the designed observer and controller are either mode-dependent or mode-independent;

· consideration of robust H filtering in terms of uncertain TRM or filter parameters leading to a method for totally mode-independent filtering

· development of LMI-based conditions for a class of adaptive state feedback controllers with almost-certainly-bounded estimated error and almost-certainly-asymptotically-stable corres

ponding closed-loop system states · applications of Markov process on singular systems with norm bounded uncertainties and time-varying delays

Analysis and Design of Singular Markovian Jump Systems contains valuable reference material for academic researchers wishing to explore the area. The contents are also suitable for a one-semester graduate course.

Expands reader understanding of a class of systems important in control of electrical, economic, chemical-process and mechanical systems Gives examples of application in two classes of singular system Suitable for use as instructional material in a one-semester graduate course Includes supplementary material: sn.pub/extras

Auteur
Guoliang Wang received the B.Sc., M.Sc. and Ph.D. degrees in Control Theory and Engineering from the Northeastern University, China, in 2004, 2007 and 2010, respectively. He is currently an Associate Professor in the School of Information and Control Engineering, Liaoning Shihua University, China. He has authored/co-authored over 40 publications. His research interests include Markovian jump systems, singular systems, stochastic control and filtering.Qingling Zhang received the B.Sc. and M.Sc. degrees from the Mathematics Department and the Ph.D. degree from the Automatic Control Department of Northeastern University, China, in 1982, 1986, and 1995, respectively. Since 1997, he has been a Professor with Northeastern University. He is also a member of the University Teaching Advisory Committee of National Ministry of Education. He has published 16 books and more than 480 papers about control theory and applications. Dr. Zhang received 14 prizes from central and local governments for his research. He has also received the Golden Scholarship from Australia in 2000 and now holds a visiting professor position in the University of Kent awarded by the Royal Academy of Engineering in United Kingdom. His current research interests cover singular systems, networked control systems, stochastic control and robust control.Xinggang Yan received the B.Sc. and M.Sc. degrees in Shaanxi Normal University and Qufu Normal University respectively, and received the Ph.D degree in Control Engineering from the Automatic Control Department of Northeastern University, China, in 1997. Currently, he is a Lecturer in the School of Engineering and Digitalk Arts in the University of Kent. He is a member of IEEE. He has published more than 100 papers in the area of control theory and applications. His research interest includes nonlinear control, sliding mode control, decentralized control, time delay systems, observer design and fault detection and isolation.

Contenu
Introduction.- Stability.- Stabilization.- H-infinity Control.- Observer-based Feedback Stabilization.- Filtering.- Adaptive Control.- Applications of a Markov Process.