A model-free adaptive predictive path-tracking controller with PID terms for tractors

Abstract

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.