Abstract
An optimal adaptive fuzzy controller is designed to achieve more stringent levels of comfort for a half-body car model. This aim will be fulfilled by reducing road disturbances and decreasing the acceleration of the body. The proposed controller consists of two adaptive fuzzy controllers with two fuzzy systems. Each one has two inputs, one output and twenty five linguistic fuzzy IF-THEN rules. Every input has five Gaussian membership functions and uses the product inference engine, singleton fuzzifier and the centre average defuzzifier. In order to determine the optimal parameters for the Adaptive Fuzzy Controller (AFC), the Gravitational Search Algorithm (GSA) is applied. The relative displacement between spring mass and tire, along with the acceleration of the body, are the two objective functions being applied in the optimization algorithm. The results illustrate the superiority of the proposed optimal adaptive fuzzy controller in comparison with traditional controllers.
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