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This research introduces an optimal adaptive fuzzy controller consisting of two fuzzy systems each including 1 output, 2 inputs, and 25 fuzzy rules. The designed fuzzy sytems, in turn, comprises Gaussian membership functions and applies the singleton fuzzifier, center average defuzzifier, and product inference engine. Moreover, the Gravitational Search Algorithm (GSA) is utilized to ascertain the optimum parameters of the controller. The body acceleration and the relative displacement between the tire and the sprung mass are utilized to form a proper objective function in the optimization procedure. Results show the dominance of the proposed approach over the conventional controllers.

Optimum Design of an Adaptive Fuzzy Controller as Active Suspension for a Quarter-Car Model