Authors

Abstract

With the development of agricultural automation, applying intelligent algorithms to the navigation control of agricultural work vehicles has important practical significance for improving vehicle navigation accuracy and operation efficiency. In view of the complexity of the agricultural greenhouse environment, this study proposed a fuzzy PID path tracking algorithm based on the traditional vehicle PID control system. This algorithm uses a fuzzy controller to improve the PID control system, thereby realizing the online setting of PID control parameters. In order to verify the effectiveness of the fuzzy PID path tracking algorithm, the improved control system was applied to the tracked vehicle robot of S University, and the operation performance of the vehicle robot was tested. The research results show that the absolute error rate of vehicle robot distance measurement is less than 1%; the error of the man-machine follow-up test is between 4 and 7 cm, and the measured follow-up distance is slightly less than the safe follow-up distance; the maximum error of the vehicle's fixed-point parking is 0.3 cm; The linear position tracking control has a lateral position deviation of ±3cm, and the vehicle's linear driving control and steering effects are better. The fuzzy PID path tracking algorithm designed this time shows good control performance, which has reference significance for the practical application of agricultural robots.

Abstract in Chinese

随着农业自动化的发展，将智能算法应用于农业作业车辆的导航控制，对于提高车辆导航精度和作业效率具有重要的现实意义。针对农业温室环境的复杂性，本文在传统车辆PID控制系统的基础上，提出了一种模糊PID路径跟踪算法。该算法采用模糊控制器对PID控制系统进行改进，从而实现PID控制参数的在线整定。为了验证模糊PID路径跟踪算法的有效性，将改进后的控制系统应用于S大学履带式车辆机器人，并对其运行性能进行了测试。研究结果表明，车载机器人测距的绝对误差率小于1%；人机跟踪试验的误差在4～7cm之间，实测跟踪距离略小于安全跟踪距离；车辆定点停车最大误差为0.3cm；直线位置跟踪控制具有±3cm的横向位置偏差，车辆的线性驾驶控制和转向效果较好。本次设计的模糊PID路径跟踪算法具有良好的控制性能，对农业机器人的实际应用具有参考意义。