Multi-machine Collaborative Control Method of Agricultural Machinery Formation Transfer Based on Fuzzy Algorithm
Abstract
Aiming at the problems of slow response speed, low control accuracy, poor stability, and insufficient robustness caused by the influence of complex environment of collaborative control in agricultural machinery transfer scenarios, a multi-machine collaborative control method is proposed for agricultural machinery formation transfer. The multi-machine collaborative model was constructed in which the host machine drived and navigated manually and the slave machines followed automatically. Based on the Frenet coordinate transformation, the collaborative control was decoupled into horizontal and vertical control, and the longitudinal controller was designed by using the model predictive control algorithm to achieve the maintenance of the relative distance and the following of speed and acceleration among the units, and the horizontal controller was designed by using the pure tracking algorithm to achieve the slave machines to follow the trajectory of the host machine and the introduction of fuzzy algorithm adjusted the key control coefficients to optimize the control effect in real time. Based on the CarSim/Simulink platform to design a variety of transfer typical working conditions on the designed method for simulation test analysis, comparisons showed that compared with the traditional control methods it had a more reliable and superior performance, and based on the intelligent tractor unit to carry out the real vehicle test verification, the results showed that the relative speed error was less than 0.570 m/s, the relative distance error was less than 0.169 m, the acceleration error was less than 0.252 m/s2 ,the lateral error was less than 0.090 m, all of them can gradually and steadily meet the actual needs of agricultural machinery formation transfer.
Keywords: agricultural machinery transfer, multi-machine collaborative, pure pursuit algorithm, model predictive control algorithm, fuzzy algorithm
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MENG Zhijun, WANG Hao, FU Weiqiang, et al. Research status and prospects of agricultural machinery autonomous driving [J] . Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(10) : 1 -24. (in Chinese)
CAO Ruyue, LI Shichao, WEI Shuang, et al. Remote monitoring platform for multi-machine cooperation based on Web - GIS [j]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(Supp. ) ; 52 -57,14. (in Chinese)
ZHANG Yingxue, CHEN Meng, CHEN Jinbao, et al. Research progress of intelligent cooperative technology for multiple robots [J] . Manned Spaceflight, 2021 , 27(6) ; 767 -778. (in Chinese)
TAN Wei, HU Yongjiang, LI Wenguang, et al. A survey of multi-UAV cooperative mission planning [J ]. Microcomputer Applications, 2021 , 37(9) : 189 - 192. (in Chinese)
LIU Chengliang, UN Hongzhen, LI Yanming, et al. Analysis on status and development trend of intelligent control technology for agricultural equipment [J ]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(1); 1-18. (in Chinese)
BAl Xiaoping, HU Jingtao, WANG Zhuo. Slave positioning method for cooperative navigation of combine harvester group based on visual servo [J] . Transactions of the CSAE, 2016, 32(24) ; 59 -68. (in Chinese)
ZHAl Zhiqiang, WANG Xiuqian, WANG Liang, et al. Collaborative path planning for autonomous agricultural machinery of master-slave cooperation [ J]. Transactions of the Chinese Society for Agricultural Machinery, 2021 , 52 ( Supp. ) ; 542 -547.(in Chinese)
l Yashuo, ZHAO Bo, XU Minghan, et al. Evaluating operation benefit of agricultural machinery using semi-supervised BP_ Adaboos [ J]. Transactions of the CSAE, 2023, 39(23) ; 67 -74. (in Chinese)
DOU Hanjie, CHEN Zhenyu, ZHAl Changyuan, et al. Research progress on autonomous navigation technology for orchard intelligent equipment [ J ]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(4) :1 -22. (in Chinese)
NOGUCHI N, WILL J, REID J, et al. Development of a master-slave robot system for farm operations[ J ]. Computers and Electronics in Agriculture, 2(X)4, 44( 1) : 1-19.
ZHANG Man, JI Yulian, LI Shichao, et al. Research progress of agricultural machinery navigation technology [ J ]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(4) ; 1 - 18. (in Chinese)
MA Z, CHONG К, MA S, et al. Control strategy of grain truck following operation considering variable loads and control delay [J]. Agriculture, 2022, 12( 10) : 1545.
XU Guangfei, CHEN Meizhou, MIAO Hequan, et al. Following operation control method of farmer machinery based on model predictive control [ J ]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51 ( Supp. 2) ; 11 -20. (in Chinese)
ZHANG Wenyu, ZHANG Zhigang, LUO Xiwen, et al. Position-velocity coupling control method and experiments for longitudinal relative position of harvester and grain truck [J ]. Transactions of the CSAE, 2021 , 37(9) ; 1-11. (in Chinese)
ZHU Zhongxiang, SONG Zhenghe, XIE Bin, et al. Automatic control system of tractors platooning [ J ]. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(8): 149 - 154. (in Chinese)
BAI Xiaoping, WANG Zhuo, HU Jingtao, et al. Harvester group corporative navigation method based on leader - follower structure; [J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(7) ; 14-21. (in Chinese)
OKU DA K, KAJIWARA Y, TERASHIMA K. A survey of technical trend of ADAS and autonomous driving [ С ]//Technical Papers of 2014 International Symposium on VLSI Design, Automation and Test. IEEE, 2014: 1 -4.
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