Design and Experiment of an Automatic Leveling System for Tractor-Mounted Implements

The body roll of the tractor propagates through its rigid hitch system to the mounted implement, causing asymmetrical soil penetration depths between the implement's lateral working elements, which affects the operational effectiveness of the implement. To address this issue, this study developed an automatic leveling system based on a dual closed-loop fuzzy Proportional-Integral-Derivative (PID) algorithm for tractor-mounted implements. The system employed an attitude angle sensor to detect implement posture in real time and utilized two double-acting hydraulic cylinders to provide a compensating torque for the implement that is opposite to the direction of the body's roll. The relationship model between the implement's roll angle and the actuator's response time was established. The controller performed implement leveling by regulating the spool position and holding time of the solenoid directional valve. Simulink simulations showed that under the control of the dual closed-loop fuzzy PID algorithm, the implement's roll angle adjusted from 10° to 0° in 1.72 s, which was 56.89% shorter than the time required by the fuzzy PID algorithm, with almost no overshoot. This demonstrates that the dual closed-loop fuzzy PID algorithm outperforms the traditional fuzzy PID algorithm. Static tests showed the system adjusted the implement roll angle from ±10° to 0° within 1.3 s. Field experiments demonstrated that the automatic leveling system achieved a maximum absolute error (<i>MaxAE</i>) of 0.91°, a mean absolute error (<i>MAE</i>) of 0.19°, and a root mean square error (<i>RMSE</i>) of 0.28°, with errors within 0.5° for 92.52% of the time. Results from terrain mutation tests indicate that under a sudden 5° vehicle roll angle change, the system confines implement deviation to ±1.5°. The system exhibits high control precision, stability, and robustness, fulfilling the demands of tractor-mounted implement leveling.

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Publication Details

Journal
Sensors
Published
2025-06-13
DOI
https://doi.org/10.3390/s25123707
Citations
2
Primary Topic
Soil Mechanics and Vehicle Dynamics
Type
article
Field-Weighted Citation Impact
1.91

Funders

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article

Design and Experiment of an Automatic Leveling System for Tractor-Mounted Implements

Engen Zhang, Haibin Yao, Yufei Liu, Juan Du et al.
2 citations
Sensors
Soil Mechanics and Vehicle Dynamics
1.91
article

Design and Experiment of an Automatic Leveling System for Tractor-Mounted Implements

Engen Zhang, Haibin Yao, Yufei Liu, Juan Du, Xiang Yin
article en
2 citations

Abstract

The body roll of the tractor propagates through its rigid hitch system to the mounted implement, causing asymmetrical soil penetration depths between the implement's lateral working elements, which affects the operational effectiveness of the implement. To address this issue, this study developed an automatic leveling system based on a dual closed-loop fuzzy Proportional-Integral-Derivative (PID) algorithm for tractor-mounted implements. The system employed an attitude angle sensor to detect implement posture in real time and utilized two double-acting hydraulic cylinders to provide a compensating torque for the implement that is opposite to the direction of the body's roll. The relationship model between the implement's roll angle and the actuator's response time was established. The controller performed implement leveling by regulating the spool position and holding time of the solenoid directional valve. Simulink simulations showed that under the control of the dual closed-loop fuzzy PID algorithm, the implement's roll angle adjusted from 10° to 0° in 1.72 s, which was 56.89% shorter than the time required by the fuzzy PID algorithm, with almost no overshoot. This demonstrates that the dual closed-loop fuzzy PID algorithm outperforms the traditional fuzzy PID algorithm. Static tests showed the system adjusted the implement roll angle from ±10° to 0° within 1.3 s. Field experiments demonstrated that the automatic leveling system achieved a maximum absolute error (<i>MaxAE</i>) of 0.91°, a mean absolute error (<i>MAE</i>) of 0.19°, and a root mean square error (<i>RMSE</i>) of 0.28°, with errors within 0.5° for 92.52% of the time. Results from terrain mutation tests indicate that under a sudden 5° vehicle roll angle change, the system confines implement deviation to ±1.5°. The system exhibits high control precision, stability, and robustness, fulfilling the demands of tractor-mounted implement leveling.

SensorsVol. 25(12)
Shandong University of Technology (CN), Zhejiang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 15%
Soil Mechanics and Vehicle Dynamics
1.91
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