This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi-Sugeno (T-S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T-S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also:

• introduces basic concepts of fuzzy sets, logic and inference system;
• discusses important properties of T-S fuzzy systems;
• develops offline and online identification algorithms for T-S fuzzy systems;
• investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T-S fuzzy systems;
• develops adaptive control algorithms for discrete-time input-output form T-S fuzzy systems with much relaxed design conditions, and discrete-time state-space T-S fuzzy systems; and
• designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T-S fuzzy systems.

Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.