Model-based fuzzy control uses a given conventional or a fuzzy open loop of the plant under control in order to derive the set of fuzzy if-then rules constituting the corresponding fuzzy controller. Furthermore, of central interest are the consequent stability, performance, and robustness analysis of the resulting closed loop system involving a conventional model and a fuzzy controller, or a fuzzy model and a fuzzy controller. The major objective of the model-based fuzzy control is to use the full available range of existing linear and nonlinear design of such fuzzy controllers which have better stability, performance, and robustness properties than the corresponding non-fuzzy controllers designed by the use of these same techniques.

State-of-the-art description of the fuzzy approach to modern nonlinear control Shows clearly the relationship between fuzzy and conventional control and the variety of ways in which the two enrich eachother

Inhalt
Stability Analysis of Fuzzy Models.- Global Stability Analysis of Second-Order Fuzzy Systems.- Quadratic Stability of Continuous-Time Fuzzy Control Systems.- Fuzzy Stability Analysis of Fuzzy Systems: A Lyapunov Approach.- Inverse Fuzzy Models.- Inverse Fuzzy Process Models for Robust Hybrid Control.- Inverse Fuzzy Model Based Predictive Control.- Adaptive Fuzzy Control.- Stable Adaptive Control Using Fuzzy Systems and Neural Networks.- An Adaptive Fuzzy Sliding-Mode Controller.- Discrete-Time Adaptive Fuzzy Logic Control of Feedback Linearizable Systems.- Fuzzy Model Reference Learning Control.- Predictive Fuzzy Control.- Development of a Fuzzy Relational-Based Predictive Controller.- A Simplified Fuzzy Relational Structure for Adaptive Predictive Control.- Predictive Control Based on a Fuzzy Model.- Gain Scheduled Fuzzy Control.- Transient Performance, Robustness and Off-Equilibrium Linearisation in Fuzzy Gain Scheduled Control.- Design of Fuzzy Gain Schedulers.