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SHI Yangjie, CHENG Xinhui, XI Xiaobo, et al. Research progress on the path tracking control methods for agricultural machinery navigation[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(15): 1-14. DOI: 10.11975/j.issn.1002-6819.202304004
Citation: SHI Yangjie, CHENG Xinhui, XI Xiaobo, et al. Research progress on the path tracking control methods for agricultural machinery navigation[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(15): 1-14. DOI: 10.11975/j.issn.1002-6819.202304004

Research progress on the path tracking control methods for agricultural machinery navigation

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  • Received Date: April 01, 2023
  • Revised Date: July 02, 2023
  • Available Online: September 05, 2023
  • Agricultural production mode has been required for the intelligence and digitization of agricultural machinery. An automatic control system has gradually been the research interest of agricultural machinery in recent years. Among them, the navigation system with path tracking control can be expected to improve the accuracy of the agricultural machinery and the adaptability to the environment. Specifically, the accuracy and efficiency of agricultural production can be improved to realize more complex tasks, in order to avoid the wide crop coverage due to leakage testing. In this review, the types of agricultural machinery models were evaluated with/without the navigation path tracking control system. Three categories were also divided into the path-tracking control system with the kinematic or dynamic models, as well as the model-independent path-tracking control. Agricultural machinery was assumed as a rigid or single rigid body system for control with the kinematic model. The kinematic model of agricultural machinery included pure tracking, linear quadratic optimal control, and the model predictive control. By contrast, the dynamic model of agricultural machinery considered the influence of the mass and inertia of agricultural machinery on the control, particularly with the sliding mode variable structure control. The path-tracking control method unrelated to the agricultural machinery model was utilized to directly extract the features from the sensor data or visual information. The PID, and fuzzy control were the widely-used path-tracking control systems in the path-tracking control methods unrelated to the agricultural machinery model. The optimal path-tracking control of the agricultural machinery was achieved to correct the control system using the error between the sensor feedback and reference input values. The pros and cons of various control methods were clarified to evaluate the existing solutions. The current research progress was reviewed on the general and specific existing solutions to the navigation path tracking control of agricultural machinery. The applicability of various control methods was also evaluated for the current development status of agricultural machinery navigation products. The development prospects were then proposed for a navigation path tracking control of agricultural machinery. Some recommendations were as follows: 1) The current model was limited to describing the motion process of agricultural machinery. There was a high demand for the high precision model research of agricultural machinery; 2) In order to improve the adaptability and robustness of the control method, the research should be extended from the conventional to extreme and complex conditions; 3) The single control method was confined in the navigation path tracking control method of agricultural machinery. It can be expected to require the development trend of multi-method fusion control. This finding can provide strong references for subsequent research on the path-tracking control methods, particularly for the intelligent development of agricultural machinery in China.

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