Research on LQR Control Strategy Optimization Based on Genetic Algorithm for Active Suspension
To improve the ride comfort and handling stability of the active suspension system,a method for finding the optimal weight matrix parameters using a linear quadratic regulator(LQR)with genetic algorithm is proposed.This control algorithm over-comes the shortcomings of the weighted matrices Q and R determined by empirical subjectivity in the traditional LQR control method,so that it can achieve the optimal control effect.In this paper,a 1/4 vehicle active suspension model and road input model are first established,and the LQR controller optimized by genetic algorithm is applied to the active suspension system.Tak-ing the active suspension as the control objective,the vertical acceleration of the body,the dynamic deflection of the suspension spring and the tire dynamic displacement are assessment indices,through simulation analysis,compared with the passive control and the LQR-controlled active suspension system,this optimization algorithm can significantly reduce the vertical acceleration of the body and the dynamic deflection of the suspension spring,while the tire dynamic displacement has little effect,thus verifying the effectiveness of the control method.