Optimal design of fuzzy logic controller for multi-body model of semi-active suspension based on genetic algorithm

This paper presents a novel control scheme for the multi-body semi-active suspension system. The proposed scheme is composed of two parts: a multi-body model of the semi-active suspension system and a genetic algorithm-based fuzzy logic controller. With the fast development of computers, multi-body model and multi-body systems dynamics are applied to a broad variety of engineering problems. In this work, ADAMS software is utilized to complete the multi-body model of a full car semi-active suspension system. In order to control the suspension system efficiently, a fuzzy logic controller is developed in MATLAB/Simulink environment. The kernel of the fuzzy logic controller is a set of linguistic control rules. The conventional fuzzy control rules are established by the knowledge and experience of expertise or skilled operator. In other words, the rules are dependent on the knowledge and the experience of expertise, and may not be optimal. So, in this paper, a fuzzy logic controller is developed to generate the rule table automatically based on the improved genetic algorithm. To verify the performance of the genetic algorithm-based controller, simulations were simulated with random road profile at two different speeds, 25m/sec and 35m/sec, to demonstrate the effectiveness of the proposed control system in comparison with the passive suspension response. It was shown that this developed fuzzy logic controller based on genetic algorithm enhances the performance of the full car suspension system significantly. This control system is suitable for the multi-body model and can be extended to other applications of the mechanical systems.