Development of a Depth Control System Based on Variable-Gain Single-Neuron PID for Rotary Burying of Stubbles
Abstract
:1. Introduction
2. Materials and Methods
2.1. Depth Control System Structure
2.2. Kinematic Model of the Depth Control System
2.3. The Design of Controller
2.3.1. Electronic-Control Proportional Hydraulic Valve
2.3.2. Variable-Gain Single-Neuron PID Controller
3. Results and Discussion
3.1. MATLAB Simulation Analysis
3.2. Field Experiment
- Check the status of the implement to ensure the normal operation of the electric control system and hydraulic system;
- Set the burying depth control algorithm;
- Set up the RTK-GNSS base station as shown in shown in Figure 11, and set the GNSS positioning coordinate origin and communication port to start the rotary burying depth control system;
- Start the operation;
- Record test data including height changes of the tractor and the rotary tiller; and
- Repeat steps 2 to 5 using three different control algorithms.
- Tillage depth and stability coefficient of tillage depth
- 2.
- Burying rate of stubbles
4. Conclusions
- (1)
- To solve the problems of slow response speed and inaccurate depth control of the existing rotary burying operation unit, a depth control system based on variable-gain single-neuron PID was designed and implemented. The main instruments of the depth control system included an RTK-GNSS, an electric-control proportional hydraulic valve, an STM32 microcontroller, an on-board computer, an angle sensor, and a rotary tiller for stubble burying.
- (2)
- When the height of the field surface changed, the driver’s experience could not accurately control the depth of the rotary tillage operation, which increased the difficulty of the operation and affected the growth of later crops. A dual antenna RTK-GNSS was used to obtain the real-time surface height and roll angle, and the height changes at the center point of the rotary tiller during the operation. These values are then sent to the variable-gain single-neuron PID control algorithm to obtain the ideal lifting angle of the three-point hitch lifting arm. Finally, the STM32 microcontroller could change the lifting angle of the lift arm in real-time through the electronic-control proportional hydraulic valve.
- (3)
- Simulink simulation results showed that the variable-gain single-neuron PID could alleviate the slow convergence rate and the large overshoot of the conventional PID, improve the adaptability of the scale factor K to increase the response speed of the controller, and improve the adaptability of the rotary burying depth control system to complex field surface conditions.
- (4)
- Field experiment results showed that compared to the conventional PID and single-neuron PID control algorithms, the variable-gain single-neuron PID control algorithm adjusted the scale factor K in real-time, making the rotary tiller follow the real-time changes of the field surface better, enhancing the adaptability and robustness of the rotary burying depth control system. When the working speed was 0.61 m/s, the variable-gain single-neuron PID could satisfy the tillage depth requirement. The stability coefficient of the tillage depth was 96.09%, which was higher than that of the conventional PID and single-neuron PID. The straw coverage rate was 94.74%, and the overall rotary burying effect was better than those of the conventional PID and single-neuron PID. The straw rotary burying depth control system designed in this study could improve the stability of the rotary burying operation and could be used for an automatic tractor-rotary tiller stubble burying system under unmanned driving.
5. Patents
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameters | Values |
---|---|
Overall dimensions/(mm × mm × mm) | 1345 × 2500 × 1300 |
Overall weight/kg | 750 |
Working width/mm | 2300 |
Rotary burying depth/mm | 120~180 |
Matching power/kW | ≥65 |
Rotary knives | 54 |
Helical cross knives | 18 |
Machetes | 36 |
Index | Value | |
---|---|---|
Stubble height/cm | 58 | |
Stubble coverage/g.m−2 | 1273 | |
Soil firmness/kPa | 1528 | |
Soil moisture content/% | 36.40 | |
Particle size distribution/% | (0, 0.002] mm | 42.03 |
(0.002, 0.05] mm | 55.06 | |
(0.05, 2] mm | 2.91 |
Algorithm | Average Depth of Rotary Burying/cm | Stability Coefficient of Rotary Burying Depth/% | Burying Rate of Stubble/% |
---|---|---|---|
Conventional PID | 15.05 | 90.24 | 90.36 |
Single neuron PID | 15.23 | 91.72 | 91.25 |
Variable-gain single-neuron PID | 15.49 | 96.09 | 94.74 |
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Zhou, M.; Xia, J.; Zhang, S.; Hu, M.; Liu, Z.; Liu, G.; Luo, C. Development of a Depth Control System Based on Variable-Gain Single-Neuron PID for Rotary Burying of Stubbles. Agriculture 2022, 12, 30. https://doi.org/10.3390/agriculture12010030
Zhou M, Xia J, Zhang S, Hu M, Liu Z, Liu G, Luo C. Development of a Depth Control System Based on Variable-Gain Single-Neuron PID for Rotary Burying of Stubbles. Agriculture. 2022; 12(1):30. https://doi.org/10.3390/agriculture12010030
Chicago/Turabian StyleZhou, Mingkuan, Junfang Xia, Shuai Zhang, Mengjie Hu, Zhengyuan Liu, Guoyang Liu, and Chengming Luo. 2022. "Development of a Depth Control System Based on Variable-Gain Single-Neuron PID for Rotary Burying of Stubbles" Agriculture 12, no. 1: 30. https://doi.org/10.3390/agriculture12010030
APA StyleZhou, M., Xia, J., Zhang, S., Hu, M., Liu, Z., Liu, G., & Luo, C. (2022). Development of a Depth Control System Based on Variable-Gain Single-Neuron PID for Rotary Burying of Stubbles. Agriculture, 12(1), 30. https://doi.org/10.3390/agriculture12010030