Identification of MIMO systems by input-output TS fuzzy models

Abstract

A number of techniques have been introduced to construct fuzzy models from measured data. Most attention has been focused on multiple-input, single-output (MISO) systems. This article concentrates on the identification of multiple-input multiple-output (MIMO) systems by means of product-space fuzzy clustering with adaptive distance measure (the Gustafson-Kessel algorithm). The MIMO model is represented as a set of coupled input-output MISO models of the Takagi-Sugeno type. Knowledge of the physical structure can easily be incorporated in the structure of the model. Software implementation in the form of a MATLAB toolbox is briefly described. A simulation example of four cascaded tanks is given.