Hybrid Particle Swarm Optimization Genetic LQR Controller for Active Suspension

In this paper, a hybrid particle swarm optimization genetic algorithm LQR controller is used on quarter car model with an active suspension system. The proposed control utilized to overcome the shortcoming that weight matrix Q and R determined by experience in traditional method. method makes it possible achieve optimal effect. A full-order state observer observe of suspension. road input are presented at first, based system control. Sprung mass acceleration, deflection, tire dynamic load selected as effect evaluation index. Next, simulation results presented. According results, compared passive control, there obvious reduction sprung optimized under case 1 2. Simultaneously, fed back can effectively reflect true