An efficient tractor path-tracking method can increase the operational accuracy, improve land utilisation, and more efficiently provide services for autonomous tractors and precision agriculture. In this study, a model-free adaptive predictive control-proportional-integral-derivative (MFAPC-PID) method was devised. Based on preview theory, a tracking system based on course deviation angle was designed. After the tracking system was linearised, an MFAPC tracking system was developed, and its inherent defects were analysed. Referring to the control structure of an incremental PID algorithm, the MFAPC was considered as an adaptive integral item, and the MFAPC-PID controller was obtained by adding adaptive proportional and differential terms. To verify the proposed controller, collaborative simulation and hardware-in-the-loop tests were performed. The controller was simulated and tested under different paths, road surfaces, and tractor models. Compared with other methods, the MFAPC-PID path-tracking method exhibits superior comprehensive performance, adaptability, universality, and robustness. Moreover, the MFAPC-PID method is insensitive to external interference and model changes of controlled objects.

中文翻译：

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用于拖拉机的具有 PID 项的无模型自适应预测路径跟踪控制器

高效的拖拉机路径跟踪方法可以提高作业精度，提高土地利用率，更高效地为自主拖拉机和精准农业提供服务。在本研究中，设计了一种无模型自适应预测控制比例积分微分（MFAPC-PID）方法。基于预演理论，设计了基于航向偏差角的跟踪系统。跟踪系统线性化后，开发了MFAPC跟踪系统，并分析了其固有缺陷。参考增量PID算法的控制结构，将MFAPC视为自适应积分项，加入自适应比例项和微分项，得到MFAPC-PID控制器。为了验证所提出的控制器，进行了协作仿真和硬件在环测试。控制器在不同路径、路面、拖拉机型号下进行了仿真和测试。与其他方法相比，MFAPC-PID路径跟踪方法表现出优越的综合性能、适应性、普适性和鲁棒性。而且，MFAPC-PID方法对外界干扰和被控对象模型变化不敏感。