Introduction

Abstract This book presents new approaches to the construction of fuzzy models for model-based control. New model structures and identification algorithms are described for the effective use of heterogenous information in the form of numerical data, qualitative knowledge and first-principle models. By exploiting the mathematical properties of the proposed model structures, such as invertibility and local linearity, new control algorithms have been developed which are closely related to inverse model-based control, model predictive control, block-oriented model-based control, and multiple model adaptive control. In this chapter the background and the concept of this framework are described.