Introduction

Abstract

This book addresses the modeling of complex, nonlinear, or partially unknown systems by means of techniques based on fuzzy set theory and fuzzy logic. This approach, termed fuzzy modeling, is shown to be able to cope with systems that pose problems to conventional techniques, mainly due to nonlinearities and lack of precise knowledge about these systems. Methods are described for the development of fuzzy models from data, and for the design of control systems which make use of an available fuzzy model. The presented framework allows for an effective use of heterogeneous information in the form of numerical data, qualitative knowledge, heuristics and first-principle models for the building, validation and analysis of models, and for the design of controllers. The obtained model can be a part of a real-time control algorithm, or can serve for analysis of the process, in order to gain better understanding, and to improve the operation, monitoring and diagnosis.