The invention discloses a neural network PID steering control method for a hydrostatic drive tracked vehicle, which comprisesthe following steps: S1, reading a driver target relative steering radius rho ref and a target vehicle speed vref adjusted by a steering control coordination control strategy, S2, determining whether a driver vehicle is driving straightly, if yes, executing a straight driving control subprogram, and inputting the result into a neural network PID controller to be calculated, adjusting and sending pump and motor displacement instructions, and if the result is not the straight driving, judging R to be equal to 0.5 B. According to the control method, after self-adaptive adjustment of the neural network is added, the problem that adjustment of a speed adjusting scheme lags behind is solved, the steering controller can pre-judge the steering state of the vehicle, and the target vehicle speed of a driver is corrected in advance; the corrected input signal of the driver can enable the vehicle to quickly and safely steer under the conditions of no sideslip, no slipping and system pressure meeting the maximum pressure limit.
本发明公开了静液驱动履带车辆神经网络PID转向控制方法,包括以下步骤:S1:读取转向控制协调控制策略调整过的驾驶员目标相对转向半径ρref和目标车速vref,S2:判断驾驶员车辆是否直驶,如为直驶执行直驶控制子程序,并将结果输入至神经网络PID控制器计算,调节发送泵、马达排量指令,如不为直驶判断R=0.5B。本发明的控制方法加入神经网络的自适应调节之后,解决了调速方案调节滞后的问题,转向控制器可对车辆转向状态进行预判,提前修正驾驶员目标车速,修正后的驾驶员输入信号可使得车辆在无侧滑、打滑、系统压力满足最高压力限制的条件下进行迅速安全转向。
Neural network PID steering control method for hydrostatic drive tracked vehicle
静液驱动履带车辆神经网络PID转向控制方法
2021-04-23
Patent
Electronic Resource
Chinese
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