Constructing fuzzy controllers with B-spline models?Principles and applications

摘要

In this paper we present an approach to designing a novel type of fuzzy controller. B-spline basis functions are used for input variables and fuzzy singletons for output variables to specify linguistic terms. “Product” is chosen as the fuzzy conjunction, and “centroid” as the defuzzification method. By appropriately designing the rule base, a fuzzy controller can be interpreted as a B-spline interpolator. Such a fuzzy controller may learn to approximate any known data sequences and to minimize a certain cost function. By choosing such a function appropriately, the learning process can be made to converge rapidly. We applied this approach to the problems of function approximation and both supervised and unsupervised learning of mobile robots. Experiments validate the advantages of this approach. © 1998 John Wiley & Sons, Inc.13: 257–285, 1998