基于强化学习的轨迹跟踪控制算法研究OA

A model predictive control algorithm based on reinforcement learning is proposed for the trajectory tracking control problem of intelligent vehicles.An intelligent body in reinforcement learning is used to replace the prediction model,predict the op-eration decision of the future moment,design the trajectory tracking control reward function,and train the intelligent body so that the control algorithm can track the target trajectory quickly and accurately.The control algorithm is built and simulated by Matlab/Simulink to track the target trajectory under low-speed and high-speed operating conditions,respectively.The results show that the model predictive controller based on reinforcement learning has better dynamic tracking characteristics,the control tracking error is smaller,and the vehicle control process is more stable.