Design and experiment of fuzzy-PID based tillage depth control system for a self-propelled electric tiller
Keywords:
fuzzy PID, self-propelled electric tiller, tillage depth, electro-controlled hydraulic system, comprehensive adjustment of force and positionAbstract
The research on the self-propelled electric tiller is vital for further improving the quality and efficiency of greenhouse rotary tillage operation, reducing the work intensity and operation risk of operators, and achieving environmentally friendly characteristics. Most of the existing self-propelled tillers rely on manual adjustment of the tillage depth. Moreover, the consistency and stability of the tillage depth are difficult to guarantee. In this study, the automatic control method of tillage depth of a self-propelled electric tiller is investigated. A method of applying the fuzzy PID (Proportional Integral Derivative) control method to the tillage depth adjustment system of a tiller is also proposed to realize automatic control. The system uses the real-time detection of the resistance sensor and angle sensor. The controller runs the electronically controlled hydraulic system to adjust the force and position comprehensively. The fuzzy control algorithm is used in the operation error control to realize the double-parameter control of the tillage depth. The simulation and experimental verification of the system are conducted. Results show that the control system applying fuzzy PID can improve the soil breaking rate by 3% in the operation process based on reducing the stability variation of tillage depth by 24%. The control strategy can reach the set value of tillage depth quickly and accurately. It can also meet the requirement of tillage depth consistency during the operation. Keywords: fuzzy PID, self-propelled electric tiller, tillage depth, electro-controlled hydraulic system, comprehensive adjustment of force and position DOI: 10.25165/j.ijabe.20231604.8116 Citation: Xiao M H, Ma Y, Wang C, Chen J Y, Zhu Y J, Bartos P, et al. Design and experiment of fuzzy-PID based tillage depth control system for a self-propelled electric tiller. Int J Agric & Biol Eng, 2023; 16(4): 116-125.References
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[33] Yang H, Xia C, Han J, Chen C, Zhang H. Model and dynamic performance analysis of mountain tractor suspension implements. IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2020; 508(1): 012194. doi:10.1088/1755-1315/508/1/012194
[34] Kim J C, Huh J H, Ko J S. Optimization design and test bed of fuzzy control rule base for PV system MPPT in micro grid. Sustainability, 2020; 12(9): 3763. doi:10.3390/su12093763
[35] Zhou X, Wang J, Huang L, Li D, Duan Q. Modelling and controlling dissolved oxygen in recirculating aquaculture systems based on mechanism analysis and an adaptive PID controller. Computers and Electronics in Agriculture, 2022; 192: 106583. doi:10.1016/j.compag.2021.106583
[36] Wang Y, Zhang D, Yang L, Cui T, Zhang W, Qi B, et al. Field performance of an electric–hydraulic control system for vibrating subsoiler with flexible tines. Computers and Electronics in Agriculture, 2020; 172: 105377. doi:10.1016/j.compag.2020.105377
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[38] Xu X M, Wang Y Qn, Wang Y W. Influence of magnetic field on sound transmission loss of Magnetorheological fluids. Materials, 2022; 15(17): 6032. doi:10.3390/ma15176032
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[40] Wu J, Ling C, Chen Y, Li Z, Song F, Raghavan G S V, et al. Monitoring and control of microwave drying with volatiles detection of celery stalks. Computers and Electronics in Agriculture, 2021; 187: 106256. doi:10.1016/j.compag.2021.106256
[2] Behera A, Raheman H. Effect of peripheral to forward speed ratio on overall performance an active tillage implement: tractor drawn rotavator. Journal of The Institution of Engineers (India): Series A, 2021; 102(4): 981-988.
[3] Du Z H, Chen Y Y, Zhang J, Han X M, Geng A J, Zhang Z L. Development status and prospect of rotary tillage machinery at home and abroad. Journal of Chinese Agricultural Mechanization, 2019; 40(4): 43-47. (in Chinese)
[4] Lin Y, Chen Q, Zhang H, Ma Y, Zeng W, Wei G, et al. Design and test of a positioning system for a greenhouse electric micro-tiller based on ultra-wideband. Mechanical Sciences, 2022; 13(1): 225-237.
[5] Maraveas C, Piromalis D, Arvanitis K G, Bartzanas T, Loukatos D. Applications of IoT for optimized greenhouse environment and resources management. Computers and Electronics in Agriculture, 2022; 198: 106993. doi:10.1016/J.COMPAG.2022.106993
[6] Nielsen S K, Munkholm L J, Lamandé M, Nørremark M, Edwards G, Green O. Seed drill depth control system for precision seeding. Computers and Electronics in Agriculture, 2018; 144: 174-180.
[7] Xia J, Li D, Liu G, Cheng J, Zheng K, Luo C. Research on electro-hydraulic monitoring system for tractor-mounted deep tillage based on angle detection. Journal of Agricultural Machinery, 2021; 52(8): 386-395.
[8] Zhou M, Xia J, Zhang S, Hu M, Liu Z, Liu G, et al. Development of a depth control system based on variable-gain single-neuron PID for rotary burying of stubbles. Agriculture, 2021, 12(1): 30. doi:10.3390/agriculture12010030
[9] Liu C, Hua B, Du Y, Li Z, Zhu Z, Mao E. Research on dynamic pressure feedback correction method of tractor electro-hydraulic suspension system. Journal of Agricultural Machinery, 2020; 51(S1): 535-541.
[10] Zhang H, Li L, Zhao J, Zhao J, Liu S, Wu J. Design and implementation of hybrid force/position control for robot automation grinding aviation blade based on fuzzy PID. The International Journal of Advanced Manufacturing Technology, 2020; 107(3): 1741-1754.
[11] Wang Z, Zou L, Su X, Luo G, Li R, Huang Y. Hybrid force/position control in workspace of robotic manipulator in uncertain environments based on adaptive fuzzy control. Robotics and Autonomous Systems, 2021; 145: 103870. doi:10.1016/j.robot.2021.103870
[12] Ma Y, Li R, Xu J, et al. Research on fuzzy PID automatic control strategy for tractor tillage depth. Agricultural Mechanization Research, 2019; 41(1): 241-247.
[13] Li D, Ye J, Li M, Li C, Xu H. Research on tillage depth adjustment system based on integral separation PID control. Journal of Southwest Normal University (Natural Science Edition), 2018; 43(4):121-127.
[14] Zhao G, Xia C. Research on tractor slip rate control based on SimulationX. Agricultural Mechanization Research, 2021; 43(10): 240-245.
[15] Mohammadikia R, Aliasghary M. Design of an interval type-2 fractional order fuzzy controller for a tractor active suspension system. Computers and Electronics in Agriculture, 2019, 167(C) : 105049-105049.
[16] Shafaei S M, Loghavi M, Kamgar S. A practical effort to equip tractor-implement with fuzzy depth and draft control system. Engineering in Agriculture, Environment and Food, 2019, 12(2): 191-203.
[17] Kocsis G, Xydis G. An evaluation framework on additive manufacturing for hydraulic systems in wind turbines focused on system simplification. Modelling, 2021; 2(2): 327-343.
[18] Berne L J, Raush G, Gamez-Montero P J, Roquet P, Codina E. Multi-point-of-view energy loss analysis in a refuse truck hydraulic system. Energies, 2021; 14(9): 2707. doi:10.3390/EN14092707
[19] Zhao J, Xiao M, Bartos P, Bohata A. Dynamic engagement characteristics of wet clutch based on hydro-mechanical continuously variable transmission. Journal of Central South University, 2021; 28(5): 1377-1389.
[20] Wang M, Wu Z, Huang Y. Application research of electric control system in tractor tillage depth control. Agricultural Mechanization Research, 2020; 42(2): 265-268.
[21] Wang Y, Jing H, Zhang D, Cui T, Zhong X, Yang L. Development and performance evaluation of an electric-hydraulic control system for subsoiler with flexible tines. Computers and Electronics in Agriculture, 2018; 151: 249-257.
[22] Wei W, Shang Y, Peng Y, Cong R. Prediction model of sound signal in high-speed milling of wood-plastic composites. Materials, 2022; 15(11): 3838-3848. doi:10.3390/ma15113838
[23] Wei W, Cong R, Li Y, Ayodele D A, Yang C, Chen Z. Prediction of tool wear based on GA-BP neural network. Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture, 2022, 236(12): 1564-1573.
[24] Wang Q, Zhang Q, Zhang Y, Zhou G, Li Z, Chen L. Lodged sugarcane/crop dividers interaction: analysis of robotic sugarcane harvester in agriculture via a rigid-flexible coupled simulation method. Actuators. MDPI, 2022; 11(1): 23. doi:10.3390/act11010023
[25] Hou Y, Xu X M. High-speed lateral stability and trajectory tracking performance for a tractor-semitrailer with active trailer steering. PloS One, 2022; 17(11): e0277358. doi:10.1371/journal.pone.0277358
[26] Li X, Zhu L, Gong S. Soil-cutting simulation and dual-objective optimization on tillage process parameters of micro-tiller by smoothed particle Galerkin modeling and genetic algorithm. Computers and Electronics in Agriculture, 2022; 198: 107021. doi:10.1016/j.compag.2022.107021
[27] Zhang W, Liu M, Xu L. Design and simulation of electric tractor hydraulic suspension system. Machine Tools and Hydraulics, 2022; 50(2): 93-98.
[28] Yang S, Zhang L, Zhang H, Xu F, Li G. Research on automatic measurement and control method of suspended subsoiler tillage depth. Agriculture and Technology, 2019; 39(24): 56-58.
[29] Yun J, Sun Y, Li C, Jiang D, Tao B Li G, et al. Self-adjusting force/bit blending control based on quantitative factor-scale factor fuzzy-PID bit control. Alexandria Engineering Journal, 2022; 61(6): 4389-4397.
[30] Jing H, Zhang D, Wang Y, Yang L, Fan C, Zhao H, et al. Development and performance evaluation of an electro-hydraulic downforce control system for planter row unit. Computers and Electronics in Agriculture, 2020; 172: 105073. doi:10.1016/j.compag.2019.105073
[31] Pei G, Huang J, Ai S, Yu W, Xiong A, Jin S. Design of temperature and humidity fuzzy control system based on STM32 tea infrared greening machine. Modern Electronic Technology, 2020; 43(19): 79-83.
[32] Dogruer T, Can M S. Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm. Transactions of the Institute of Measurement and Control, 2022; 44(9): 1862-1873.
[33] Yang H, Xia C, Han J, Chen C, Zhang H. Model and dynamic performance analysis of mountain tractor suspension implements. IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2020; 508(1): 012194. doi:10.1088/1755-1315/508/1/012194
[34] Kim J C, Huh J H, Ko J S. Optimization design and test bed of fuzzy control rule base for PV system MPPT in micro grid. Sustainability, 2020; 12(9): 3763. doi:10.3390/su12093763
[35] Zhou X, Wang J, Huang L, Li D, Duan Q. Modelling and controlling dissolved oxygen in recirculating aquaculture systems based on mechanism analysis and an adaptive PID controller. Computers and Electronics in Agriculture, 2022; 192: 106583. doi:10.1016/j.compag.2021.106583
[36] Wang Y, Zhang D, Yang L, Cui T, Zhang W, Qi B, et al. Field performance of an electric–hydraulic control system for vibrating subsoiler with flexible tines. Computers and Electronics in Agriculture, 2020; 172: 105377. doi:10.1016/j.compag.2020.105377
[37] Kim Y S, Siddique M, Kim W S, Kim Y J, Lee S D, Lee D K, et al. DEM simulation for draft force prediction of moldboard plow according to the tillage depth in cohesive soil. Computers and Electronics in Agriculture, 2021; 189:106368. doi:10.1016/j.compag.2021.106368
[38] Xu X M, Wang Y Qn, Wang Y W. Influence of magnetic field on sound transmission loss of Magnetorheological fluids. Materials, 2022; 15(17): 6032. doi:10.3390/ma15176032
[39] Zhu L, Ge J R, Cheng X, Peng S S, Qi Y Y, Zhang S W, et al. Modeling of share/soil interaction of a horizontally reversible plow using computational fluid dynamics. Journal of Terramechanics, 2017; 72: 1-8.
[40] Wu J, Ling C, Chen Y, Li Z, Song F, Raghavan G S V, et al. Monitoring and control of microwave drying with volatiles detection of celery stalks. Computers and Electronics in Agriculture, 2021; 187: 106256. doi:10.1016/j.compag.2021.106256
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Published
2023-10-17
How to Cite
Xiao, M., Ma, Y., Wang, C., Chen, J., Zhu, Y., Bartos, P., & Geng, G. (2023). Design and experiment of fuzzy-PID based tillage depth control system for a self-propelled electric tiller. International Journal of Agricultural and Biological Engineering, 16(4), 116–125. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/8116
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Power and Machinery Systems
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