Optimal control for automotive seat suspension system based on acceleration based particle swarm optimization

Weighting matrices of most standard LQR controllers are determined by the designers according to their experience, and that usually makes controllers unable to achieve global optimum. To deal with this problem, a method of determining weighting matrices by acceleration based particle swarm optimization (APSO) was proposed. A six degree of freedom (DOF) half car model with “seat and human” system was established in this paper. The parameters of the seat suspension were optimized by APSO, and LQR control was carried out on the basis of the parameter optimization system. In this study, MATLAB/Simulink was used for the simulation of parameter optimization system and LQR control system. The vibration isolation performance of seat suspension system was indicated by the vertical acceleration of “seat and human” with the constraint of dynamic displacement of seat suspension. Results show that the controller based on APSO has better vibration-reducing properties than the LQR controller based on GA.