为解决无人驾驶车辆轨迹跟踪精度和控制稳定性问题，提出了一种考虑前馈控制和动态调整速度比例、积分、微分(Proportional Integral Derivative，PID)控制器参数的方法。采用七次多项式进行变道轨迹规划，改进纵向位置和速度双PID控制器，动态调整纵向位移误差，并采用模糊控制对PID控制器参数进行实时整定;同时，结合基于"前馈+反馈"的线性二次型调节器(Linear Quadratic Regulator，LQR)控制算法求解横向位移误差和车身横摆角速度误差，使跟踪误差收敛，最终通过电机模型将控制量转化为期望前轮转角，解决了模型失配导致的横向位移误差较大的问题。进行仿真验证，当车辆以60 km/h的速度在城市道路场景下变道行驶时，横向位移误差控制在0。015 m范围内，纵向位移误差控制在毫米级别，误差范围控制在[0。002，0。006]m，车身横摆角速度变化平稳且横摆角速度误差不超过0。83 rad/s。在此基础上，进一步完成了实车实验，仿真与实车实验结果均表明，所设计的控制器可以达到轨迹跟踪中对高精度的要求，能够保证无人驾驶车辆在变道工况平稳行驶。
Dynamic parameter adaptive control for lane change tracking of driverless vehicles
To solve the problem of trajectory tracking accuracy and control stability of driverless vehicles,a method that considers feedforward control and dynamically adjusts speed PID controller parameters is proposed.Seven polynomial is used for lane change trajectory planning,the double PID controller of longitudinal position and speed is improved,the longitudinal displace-ment error is adjusted dynamically,and the PID parameters are adjusted in real time.Meanwhile,the lateral displacement error and the pendulum velocity error are solved,making the tracking error converge,and finally the control amount is converted into the desired front wheel angle through the motor model,thus solving the problem of large lateral tracking error caused by the mod-el mismatch.By simulation verification,when the vehicle is running in the urban road scene at 60 km/h,the transverse displace-ment error is controlled within 0.015 m,the longitudinal displacement error is controlled at mm level,and the error range is con-trolled at[0.002,0.006]m.The speed of the body is stable and the speed error is not more than 0.83 rad/s.On this basis,the real vehicle experiment is further completed.The results of both simulation and real vehicle experiment show that the designed controller can meet the requirements of high precision in trajectory tracking and ensure the smooth driving of driverless vehicles in the lane change condition.
unmanned drivingparameter-adaptiveProportional Integral Derivative(PID)fuzzy controlLinear Quadratic Regulator(LQR)trajectory tracking
国家科技期刊平台
NSTL
万方数据
