Development of Fuzzy Logic Controller by Particle Swarm Optimization Algorithm for Semi-active Suspension System using Magneto-rheological Damper

摘要

The performance of fuzzy logic (FLC) and PID controllers optimized by particle swarm optimization (PSO) for semi-active suspension system using magneto-rheological (MR) damper are investigated. MR damper is an intelligent damper filled with particle magnetic polarizable and suspended into a liquid form. The Bouc-Wen model of MR damper is used to determine the required damping force based on force-displacement and force-velocity characteristics. During this research, the scaling factors of FLC and the gain parameters of PID controller will be optimized using the intelligent PSO technique to achieve the lowest Mean Square Error (MSE) of the system response. The performance of the proposed controllers based on intelligent PSO technique will be compared with the performance of passive suspension system for the body displacement, body acceleration, tire displacement and tire acceleration. Two different disturbances namely bump and hole, and random signals is implemented into the system. The simulation results demonstrates that the PSO tuned FLC exhibits an improvement to the ride comfort and has the smallest MSE as compared to the performance of PSO tuned PID and passive suspension system.