The main aim of this book is to show that fuzzy control is not totally ad hoc, that there exist formal techniques for the analysis of a fuzzy controller, and that fuzzy control can be implemented even when no expert knowledge is available.

The main aim of this book is to show that fuzzy control is not totally ad hoc, that there exist formal techniques for the analysis of a fuzzy controller, and that fuzzy control can be implemented even when no expert knowledge is available.

This objective has already been achieved for fuzzy sliding mode controllers and fuzzy gain schedulers - the main topics of this book.

Introduction; General overview; Fuzzy identification from a grey box modeling point of view; Clustering methods; Constructing fuzzy models by product space clustering; Identification of Takagi-Sugeno fuzzy models via clustering and Hough ...

"This volume contains the thoroughly refereed and revised papers accepted for presentation at the IJCAI '91 Workshops on Fuzzy Logic and Fuzzy Control, held during the International Joint Conference on AI at Sydney, Australia in August 1991 ...

In this volume state-of-the-art fuzzy logic solutions are presented and their pros and cons are discussed in detail based on extensive experimentation on real mobile robots.

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.