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Highlights

A novel IPSO-ADRC control strategy is proposed for tillage depth regulation in self-propelled electric rotary tillers, integrating intelligent optimization with disturbance rejection.

ABSTRACT. To address the accuracy issue of tillage depth in self-propelled electric rotary tillers, this study proposes a real-time tillage depth control system based on an active disturbance rejection control (ADRC) method optimized with an improved particle swarm optimization (IPSO) algorithm. The system integrates signal data from body posture sensors to establish a mathematical model of the hybrid stepping motor and utilizes the improved particle swarm optimization algorithm to fine-tune the parameters of the state observer and nonlinear state error compensator. Additionally, new nonlinear functions are designed to enhance the control efficiency of the extended state observer and nonlinear state error compensator. The tuned ADRC control signals are employed to drive the hybrid stepping motor, enabling precise tillage depth control. To evaluate the system's performance, field experiments were conducted in a tea plantation at operating speeds of 0.72 km/h and 1.2 km/h with preset tillage depths of 50 mm and 90 mm. The experimental results indicate that the IPSO-ADRC-controlled system maintains an average tillage depth standard deviation within 0.85 mm. Compared to traditional fuzzy PID control and ADRC, IPSO-ADRC reduces the coefficient of variation (CV) in tillage stability by 83.7% and 70.0%, respectively. The IPSO-ADRC control enhances the hybrid stepping motor with faster response speed, improved tracking accuracy, and stronger anti-interference capability, significantly improving control performance and ensuring higher tillage quality in tea plantation operations.