Research on the control strategy of sideslip and hysteresis of intelligent harvesting robot

doi:10.12398/j.issn.2096-7217.2022.02.005

Abstract

Abstract: Aiming at the characteristic that the heavy-load harvesters would easily slip and sideslip and its nonlinear large-lag control system, a method of compensating the sideslip and relieving the hysteresis in path tracking for heavy-load harvesters was proposed in this paper. After establishing a kinematic model, the equivalent sideslipping angle was estimated according to the previous and the present state of the harvester, to compensate for the expected wheel steering angle. The featured state of the harvester can be predicted according to the present state and speed of the harvester to adjust the present lateral error and heading angle error to optimize the expected wheel steering angle calculated by the path tracking algorithm, which can improve the accuracy and stability when the heavy-load harvester is working. The validity of the proposed algorithm was verified by experiments at the speeds of 0.6 m/s and 1.0 m/s, respectively. The maximum lateral errors of the harvester were 8.3 cm and 13.9 cm, respectively, and the standard deviations were 3.01 cm and 4.09 cm respectively. The results show that the strategy proposed in this paper can effectively reduce the lateral error and achieve accurate path tracking control.

Key words: intelligent heavy-load harvester, pure pursuit algorithm, nonlinear, control delay, sideslip

CLC Number:

Wang Zhuoxuan, Wang Lihui, Xu Ninghui, Li Yong, Shi Jiachen. Research on the control strategy of sideslip and hysteresis of intelligent harvesting robot[J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 37-44.

References

［1］Dong S, Yuan Z H, Gu C, et al. Research on intelligent agricultural machinery control platform based on multi-discipline technology integration ［J］. Transactions of the Chinese Society of Agricultural Engineering, 2018(18): 14-19. (in Chinese)
［2］Fang G H, Chang F. Application of fuzzy control in hydraulic steering by-wire system ［J］. Machinery Design & Manufacture, 2015(1): 141-143. (in Chinese)
［3］Kralev J, Mitov A, Slavov T, et al. Robust mu-controller for electro-hydraulic steering system ［C］// IEEE Eurocon 2019-18th International Conference on Smart Technologies. IEEE, 2019.
［4］Song J J, Yang X H, Li Z, et al. Shift energy-saving tracking control research based on heavy-duty hybrid electric vehicle ［J］. Computer Simulation, 2018, 35(9): 167-171. (in Chinese)
［5］Shi G B, Zhou Q, Wang S, et al. High robust control strategy for electro-hydraulic hybrid steering system in unmanned mode ［J］. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(12): 395-402.
［6］Gong J H. Study on control system and obtain ideal steering ratio for tractor hydraulic steering by-wire system ［D］. Nanjing: Nanjing Agricultural University, 2017. (in Chinese)
［7］Du H, Wang Z, Wang Y, et al. Adaptive robust control of multi-axle vehicle electro-hydraulic power steering system with uncertain tire steering resistance moment ［J］. IEEE Access, 2018.
［8］Li S H, Yang S P. Research status of hysteretic nonlinear models ［J］. Journal of Dynamics and Control, 2006(1): 10-17. (in Chinese)
［9］Xie S L, Xie Z D, Tian S P. The learning control algorithm for nonlinear discrete system with delay ［J］. Acta Automatica Sinica, 2001(1): 18-23. (in Chinese)
［10］Benioudakis M, Burnetas A, Ioannou G. Lead-time quotations in unobservable make-to-order systems with strategic customers: Risk aversion, load control and profit maximization ［J］. China Measurement & Testing Technology, 2017, 43(5): 127-131.
［11］Wei S, Li S C, Zhang M, et al. Automatic navigation path search and turning control of agricultural machinery based on GNSS ［J］. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(Z1): 70-77. (in Chinese)
［12］Lü A T, Song Z H, Mao E R. Optimized control method for tractor automatic steering ［J］. Transactions of the Chinese Society of Agricultural Engineering, 2006, 22(8): 116-119. (in Chinese)
［13］Gao D X, Rui W. A non-delay optimal disturbance rejection control approach for nonlinear systems with external disturbances and control delay ［J］. Procedia Engineering, 2011(15): 454-458.
［14］Wei R M, Jin S J. Trajectory tracking control of mobile robot under influence of slipping and sideslipping ［J］. Transducer and Microsystem Technologies, 2019, 38(3): 117-119, 130. (in Chinese)
［15］Yoo S J. Approximation-based adaptive control for a class of mobile robots with unknown skidding and slipping ［J］. International Journal of Control Automation & Systems, 2012, 10(4): 703-710.
［16］Guo L, Ge P S, Yang X L, et al. Intelligent vehicle trajectory tracking based on neural networks sliding mode control ［C］// Proceedings 2014 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS). IEEE, 2014.
［17］Cui M Y, Sun L H, Li Y F, et al. Adaptive tracking control of wheeled mobile robots in presence of longitudinal slipping ［J］. Control and Decision, 2013, 28(5): 664-670. (in Chinese)
［18］Hou Z G, Zou A M, Cheng L, et al. Adaptive control of an electrically driven nonholonomic mobile robot via backstepping and Fuzzy approach ［J］. IEEE Transactions on Control Systems Technology, 2009, 17(4): 803-815.
［19］Tian W N. Research on lateral control algorithm of self-driving vehicle ［D］. Changchun: Jilin University, 2018. (in Chinese)
[20］Liu C L, Lin H Z, Li Y M, 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)
［21］Bai X P, Wang Z, Hu J T, 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)
［22］Zhang S Y. Simulation research on path planning and tracking control for intelligent vehicles ［D］. Changchun: Jilin University, 2018. (in Chinese)
［23］Lenain R, Thuilot B, Cariou C, et al. Model predictive control for vehicle guidance in presence of sliding: application to farm vehicles path tracking ［C］// IEEE International Conference on Robotics & Automation. IEEE, 2005.
［24］Szepe T, Assal S F M. Pure pursuit trajectory tracking approach: Comparison and experimental validation ［J］. International Journal of Robotics & Automation, 2012, 27(4): 355-363.
［25］Wang W J, Hsu T M, Wu T S. The improved pure pursuit algorithm for autonomous driving advanced system ［C］//2017 IEEE 10th International Workshop on Computational Intelligence and Applications (IWCIA). IEEE, 2017: 33-38.
［26］Zhang Z G, Luo X W, Zhao Z X, et al. Trajectory tracking control method based on Kalman filter and pure pursuit model for agricultural vehicle ［J］. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(Z1): 6-12. (in Chinese)

[1]	HUANG Chenglong, ZHANG Zhongfu, LU Zhihao, ZHANG Xiaojun, ZHU Longfu, YANG Wanneng. Leaf grading for cotton verticillium wilt based on VFNet-Improved and Deep Sort [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(2): 12-21.
[2]	YANG Liang, WANG Hui, CHEN Ruipeng, SHENG Qingkai, YUAN Zhen, XIONG Benhai. Advances in pig-specific sensors [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(2): 22-34.
[3]	XIAO Zhangna, LUO Lufeng, CHEN Mingyou, WANG Jinhai, LU Qinghua, LUO Shaoming. Detection of grapes in orchard environment based on improved YOLO-v4 [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(2): 35-43.
[4]	LI Yida, WANG Liuyang, HAN Yuxiao, LI Shuai, LI Han, ZHANG Man. Crop image autonomous acquisition system based on ROS system [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(2): 53-62.
[5]	NIE Pengcheng, QIAN Cheng, QIN Ruimiao, DENG Shuiguang, SUN Chongde, HE Yong. Development status and trends of space-air-ground integrated information sensing and fusion technology [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(2): 1-11.
[6]	Tang Yurong, Shen Mingxia, Xue Hongxiang, Chen Jinxin. Development status and prospect of artificial intelligence technology in livestock and poultry breeding [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(1): 1-16.
[7]	Yan Kai, Gao Yue, Dai Baisheng, Sun Hongmin, Yin Yanling, Shen Weizheng. Research on detection of aggressive behavior among gregarious pigs based on anchor-free temporal localization [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(1): 17-25.
[8]	Han Guofeng, , Bai Zongchun, , Li Yansen, Li Chunmei. Current approaches and applications for in ovo sexing of eggs: A review [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(1): 26-35.
[9]	Yuan Zhiyu, Zhao Yunhui, Wang Song, Zhao Zhuo, Wu Yujin, Wang Chunxin. Development and application of management and control system for intellectual sheep breeding based on Internet of Things platform [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(1): 54-61.
[10]	Li Yibai, Cao Gunagqiao. Research on the scheduling model of flying defense team based on simulated annealing algorithm [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 1-9.
[11]	Bai Xuefeng, Chang Jiangxue, Teng Zhaoli, Lu Zhixiong. Research progress on key technologies of intelligent agricultural tractors in China [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 10-21.
[12]	Liu Jianlong, Bai Zongchun, Huo Lianfei, Meng Lili, Wang Huixin. Research on temperature and humidity spatial distribution of fermented mattress based on wireless sensor network [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 22-27.
[13]	Bai Yungang, Zhu Zhongzheng, Hou Yingyong, Zhou Lichun, Xiao Maohua, Zou Xiuguo. Design and test of wireless charging module for inspection robot in chicken farm [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 45-52.
[14]	Wang Xingchen, Pan Wei, Zhou Lichun, Hou Yingyong, Petr Bartos, Xiao Maohua. Research on displacement compensation method of inspection robot based on CS-BP neural network [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 53-63.
[15]	Zhang Lei, Liu Yiting, Chen Guangming, Li Peijuan. Research on navigation and rectification of inspection robot based on ultrasonic sensor [J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2022, 3(2): 64-70.