Fuzzy-Model-Based Control, Filtering, and Fault Detection for Nonlinear Systems

Fuzzy-Model-Based Control, Filtering, and Fault Detection for Nonlinear Systems Synopsis

The book focuses on the analysis and synthesis of one-dimensional (1-D) and two-dimensional (2-D) fuzzy-model-based control systems. By exploiting available information of fuzzy systems, for example, membership functions, premise variable partition information, frequency spectrum of disturbances/faults and current/past output measurements, a basic theoretical framework is formed towards the issues of less conservative fuzzy-model-based analysis and synthesis for 1-D/2-D nonlinear systems. This is obtained by providing an in-depth study on several major topics such as membership function/piecewise Lyapunov function based stability analysis, sampled-data control, event-triggered state estimation, finite frequency control/filtering/fault detection, memory control/filtering for fuzzy systems. The comprehensive and systematic treatment of nonlinear systems based on fuzzy models is one of the major features of the book, which is particularly suitable for readers who are interested in learning fuzzy models and/or 1-D/2-D nonlinear systems. From this book, the reader can obtain the most advanced analysis and synthesis techniques for fuzzy-model-based nonlinear systems.