Optimization Design of Lateral LQR Controller for Intelligent Vehicle Based on GA-PSO
In order to solve the problem of low control accuracy and low parameter tuning efficiency caused by difficulty in selecting coefficient matrix Q and R of Linear Quadratic Regulator(LQR)in lateral control of intelligent vehicle,this paper proposed an optimization method of genetic particle mixing(Genetic Algorithm-Particle Swarm Optimization,GA-PSO).A lateral LQR controller and a feed-forward controller were designed based on the two-degree-of-freedom model of the vehicle.The coefficient matrix was optimized using the LQR controller's own energy loss function as the cost function.The algorithm optimization results of GA-PSO and PSO were compared.The CarSim/Simulink co-simulation shows that the GA-PSO optimized controller improves the tracking accuracy and computing efficiency by 47.06％and 63.54％,respectively,and the optimized controller has strong robustness.
万方数据
维普
