Research on Hybrid Control Strategy for Path Tracking of Autonomous Vehicles
F or the fact that single control algorithm cannot simultaneously meet the requirements of autonomous vehicles for path tracking accuracy and controller solving speed,this paper proposed a hybrid control strategy based on Linear Quadratic Regulator(LQR)and Model Predictive Control(MPC).The strategy used an LQR in the low-speed condition and an MPC algorithm in the high-speed condition,on the basis of which a switching mechanism of the control algorithm based on a Finite State Machine(FSM)was designed and the control parameters were optimized by Genetic Algorithm(GA).The hybrid control strategy was simulated and verified based on CarSim and MATLAB/Simulink simulation platforms,and the real vehicle test was further completed.The experimental results show that the designed hybrid control strategy can reduce the computation time on the basis of improving the tracking accuracy,and the average lateral error and average heading error are reduced by 26.3％and 39.6％,respectively,and the average computation time is reduced by 10.9％compared with the single control algorithm.
Path trackingLinear Quadratic Regulator(LQR)Model Predictive Control(MPC)Finite State Machine(FSM)Genetic Algorithm(GA)
万方数据
维普
