Springer Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems: 439 (Lecture Notes in Control and Information Sciences, 439)

This book provides readers with a coherent, structured account of state-multiplicative noisy systems. It demonstrates practical control engineering examples from various areas of the discipline to illustrate the relevance of the theoretical development. Review From the reviews:“This book is about control and estimation of state-multiplicative noisy systems … . The systems consider in this book is extended to various ones with state dependent noise. The book contains five parts. … Some Matlab codes for solving the systems given in examples are supplied in Appendix C, which will be helpful for readers to try to give some simulation. The book is suitable for graduate students and engineers.” (Kai Wang, zbMATH, Vol. 1276, 2014) From the Back Cover Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems begins with an introduction and extensive literature survey. The text proceeds to cover solutions of measurement-feedback control and state problems and the formulation of the Bounded Real Lemma for both continuous- and discrete-time systems. The continuous-time reduced-order and stochastic-tracking control problems for delayed systems are then treated. Ideas of nonlinear stability are introduced for infinite-horizon systems, again, in both the continuous- and discrete-time cases. The reader is introduced to six practical examples of noisy state-multiplicative control and filtering associated with various fields of control engineering. The book is rounded out by a three-part appendix containing stochastic tools necessary for a proper appreciation of the text: a basic introduction to nonlinear stochastic differential equations and aspects of switched systems and peak to peak  optimal control and filtering. Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems will be of interest to engineers engaged in control systems research and development to graduate students specializing in stochastic control theory and to applied mathematicians interested in control problems. The reader is expected to have some acquaintance with stochastic control theory and state-space-based optimal control theory and methods for linear and nonlinear systems.