Orthogonal least squares fuzzy modeling of nonlinear dynamical systems

This paper suggests a fuzzy modeling technique that is based on the orthogonal least squares method (OLS). In particular, the OLS is employed to perform the partition of the input space and determine the number of fuzzy rules and the premise parameters. In the sequel, a second orthogonal estimator determines the terms that will be included in the consequent part of the fuzzy rules. The tuning of the selected consequent parameters is carried out by applying the recursive least squares. The gas furnace problem, given by Box and Jenkins (1970), is used to illustrate the proposed modeling approach. Comparisons with other methods are given, where it is shown that the suggested method compares favorably with these modeling techniques