基于MPC-PID的智能电动汽车轨迹跟踪控制

Intelligent electric vehicle trajectory tracking control based on MPC-PID

由于车辆行驶过程的非线性和不确定性,智能车辆的控制器设计对轨迹跟踪性能有着重要影响。为提升智能电动汽车的轨迹跟踪精度和平稳性,提出基于瞬态搜索优化算法(TSO)的模型预测控制(MPC)和比例积分微分(PID)相结合的横纵向综合控制器。首先基于动力学模型建立车辆跟踪误差状态方程,设计横向MPC轨迹跟踪器和纵向双PID速度跟踪控制器;采用TSO算法,对MPC控制器的权重参数进行优化;通过Carsim和Matlab\Simuink联合仿真,设计不同速度区间下的行驶工况,对控制效果进行比对。仿真结果表明,经优化设计后的控制器有着更好的跟踪效果,前轮转角和横摆角速度变化平稳,可以在保证较高跟踪精度的同时兼具良好的鲁棒性。

Due to the nonlinearity and uncertainty of the vehicle's driving process,the controller design of intelligent vehicles has a significant impact on their motion and tracking performance;To improve the trajectory tracking accuracy and stability of intelligent electric vehicles,a transverse and longitudinal integrated controller combined with model predictive control(MPC)based on transient search optimization algorithm(TSO)and proportional integral differential(PID)are proposed;Firstly,based on the dynamic model,the state equation of vehicle tracking error is established,and a lateral MPC trajectory tracker and a longitudinal dual PID speed tracking controller are designed;Using TSO algorithm to optimize the weight parameters of MPC controller;Design driving conditions under different speed ranges through joint simulation using Carsim and Matlab/Simulink,and compare the control effectiveness;The comparison of simulation results shows that the optimized controller has better tracking performance,with smooth changes in front wheel angle and yaw rate.The controller can ensure high tracking accuracy while also possessing good robustness.