Tractor Path Tracking Control Method Based on Prescribed Performance and Sliding Mode Control

Liwei Zhu, Weiming Sun, Qian Zhang (), En Lu, Jialin Xue and Guohui Sha
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Liwei Zhu: School of Agricultural Engineering, Jiangsu University, No. 301 Xuefu Road, Zhenjiang 212013, China
Weiming Sun: School of Agricultural Engineering, Jiangsu University, No. 301 Xuefu Road, Zhenjiang 212013, China
Qian Zhang: School of Agricultural Engineering, Jiangsu University, No. 301 Xuefu Road, Zhenjiang 212013, China
En Lu: School of Agricultural Engineering, Jiangsu University, No. 301 Xuefu Road, Zhenjiang 212013, China
Jialin Xue: School of Agricultural Engineering, Jiangsu University, No. 301 Xuefu Road, Zhenjiang 212013, China
Guohui Sha: Weichai Lovol Intelligent Agricultural Technology Co., Ltd., Weifang 261200, China

Agriculture, 2025, vol. 15, issue 15, 1-16

Abstract: In addressing the challenges of low path tracking accuracy and poor robustness during tractor autonomous operation, this paper proposes a path tracking control method for tractors that integrates prescribed performance with sliding mode control (SMC). A key feature of this control method is its inherent immunity to system parameter perturbations and external disturbances, while ensuring path tracking errors are constrained within a predefined range. First, the tractor is simplified into a two-wheeled vehicle model, and a path tracking error model is established based on the reference operation trajectory. By defining a prescribed performance function, the constrained tracking control problem is transformed into an unconstrained stability control problem, guaranteeing the boundedness of tracking errors. Then, by incorporating SMC theory, a prescribed performance sliding mode path tracking controller is designed to achieve robust path tracking and error constraint for the tractor. Finally, both simulation and field experiments are conducted to validate the method. The results demonstrate that compared with the traditional SMC method, the proposed method effectively mitigates the impact of complex farmland conditions, reducing path tracking errors while enforcing strict error constraints. Field experiment data shows the proposed method achieves an average absolute error of 0.02435 m and a standard deviation of 0.02795 m, confirming its effectiveness and superiority. This research lays a foundation for the intelligent development of agricultural machinery.

Keywords: tractor; path tracking; prescribed performance; error constraint; sliding mode control (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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