基于改进PSO算法的拖拉机驱动防滑PID控制策略

摘要

In order to improve the trafficability of the non-road vehicles such as tractors in normal driving and working stages, this paper studied the ASR control strategy.Based on the combination of MATLAB/Simulink and Carsim,it established a trac-tor simulation model.This strategy updated the target slip rate in real time with the new method of road surface identification and used improved particle swarm optimization algorithm to adjust PID control parameters adaptively.Based on different pave-ment,a series of simulation experiments’results show that the target slip rate is changed with the vehicle driving and finally e-qual to the optimal slip rate of the pavement;based on the improved PSO algorithm,it adjusts the PID parameters rapidly,and the speed of the tractor slip rate to the target value is fast,with an average of about 1 .5 s;when driving in the docking road,it can effectively inhibit tractor from high adhesion coefficient road have just entered the low adhesion coefficient road slippery conversion rate soared,in high and low attachment coefficient road stability time are 2.63 and 1.55 seconds.%为提高拖拉机等非道路车辆在正常行驶和工作阶段的通过性，针对拖拉机ASR控制策略进行了研究。基于Carsim和MATLAB／Simulink联合建立了拖拉机仿真模型，结合新提出的路面识别方法，实时更新目标滑转率，并利用改进的粒子群算法自适应地调整PID控制参数。针对不同路面进行一系列仿真实验，结果表明，目标滑转率随车辆行驶不断更新并最终达到所处路面的最优滑转率；基于改进PSO算法的PID参数自适应调整迅速，拖拉机滑转率收敛至目标值的响应较快，平均约1．5 s；在对接路面上行驶时，能有效地抑制拖拉机从高附着系数路面刚进入低附着系数路面时滑转率骤升情况，在高、低附着系数路面的稳定时间分别为2．63 s和1．55 s。