Premise-part adaptation laws for adaptive fuzzy control and its application to vehicle speed control

Abstract

In adaptive fuzzy control, approximation accuracy of the designed fuzzy system plays a key role in the overall system performance. Up to now, a linear parameterization method has been used to derive suitable adaptive laws, even in the adaptation of premise-part membership functions. However, the premise-part adaptation schemes with linear parameterization have some fundamental limitation due to the inadequacy of the gradient algorithm for general nonlinearly parameterized functions. In the paper, a new adaptive fuzzy control method with adaptation both of the premise-part and consequence-part membership functions is presented. The proposed adaptive fuzzy control scheme does not suffer from the problems appearing in conventional premise-part adaptation by using a nongradient strategy. The global stability as well as performance enhancement is given via simulations and application results of vehicle speed control.