Model Feedforward Compensation Active Disturbance Rejection Control for a Heavy-Duty Hydraulic Manipulator Arm

doi:10.12141/j.issn.1000-565X.230115

Abstract

Abstract:

Hydraulically-driven heavy-duty manipulator arms are widely used in construction and mining machinery, and there is an urgent need for its automatic control in the industry. However, the strong parametric uncertainties and difficult-to-model dynamics of the hydraulic system and other factors bring certain challenges to its automatic control. This paper studied the position tracking control problem of a class of heavy-duty hydraulic manipulator arm driven hydraulic cylinders by taking an anchor drilling truck as an example, and proposed a model feedforward compensation active disturbance rejection controller. To solve the control problems caused by nonlinear factors such as variable load, dead zone, parametric uncertainties and friction under heavy loads, the study adopted the control method of combining model feedforward and active disturbance rejection feedback, and established the mechanism model of the system by combining the mechanism dynamics model of the heavy-duty hydraulic manipulator arm and the model of proportional valve-controlled hydraulic cylinders. Then based on the mechanism model of the system, it constructed the feedforward compensation part of the controller, and designed an extended state observer to observe the unmodeled factors of the system in real time, and the active disturbance rejection controller was constituted together with the feedback adjustments based on the state error. The experimental studies were carried out on a real heavy-duty hydraulic manipulator arm, and the results show that the model feedforward compensation active disturbance rejection controller has smaller hysteresis and tracking error than PID controller, and the overall tracking accuracy is improved by 63.5% compared with that of PID controller. This indicates that the designed controller can overcome the adverse effects of the nonlinear factors of the hydraulic system very well, and it has a higher robustness than the PID controller. Therefore, the designed control method is more suitable for the position tracking control of this kind of heavy-duty hydraulic manipulator arm.

Key words: heavy-duty hydraulic manipulator arm, feedforward control, hydraulic model, position control, extended state observer, active disturbance rejection control

CLC Number:

TP273

GUO Xinping, HE Xin, WANG Hengsheng, et al. Model Feedforward Compensation Active Disturbance Rejection Control for a Heavy-Duty Hydraulic Manipulator Arm[J]. Journal of South China University of Technology(Natural Science Edition), 2024, 52(4): 59-67.

Figures/Tables 9

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Table 1

References 24

1	ZHANG K， KANG L， CHEN X，et al ．A review of intelligent unmanned mining current situation and development trend［J］．Energies，2022，15（2）：1-19.
2	王步康．煤矿巷道掘进技术与装备的现状及趋势分析［J］．煤炭科学技术，2020，48（11）：1-11.
	WANG Bukang ．Current status and trend analysis of readway driving technology and equipment in coal mine［J］．Coal Science and Technology，2020，48（11）：1-11.
3	杨健健，张强，王超，等．煤矿掘进机的机器人化研究现状与发展［J］．煤炭学报，2020，45（8）：2995-3005.
	YANG Jianjian， ZHANG Qiang， WANG Chao，et al ．Status and development of robotization research on roadheader for coal mines［J］．Journal of China Coal Society，2020，45（8）：2995-3005.
4	王云飞，赵继云，满家祥，等．基于干扰观测器的状态受限多缸同步控制策略［J］．华南理工大学学报（自然科学版），2022，50（2）：93-101.
	WANG Yunfei， ZHAO Jiyun， MAN Jiaxiang，et al ．Multi-cylinder synchronization control strategy with state constraint based on disturbance observer［J］．Journal of South China University of Technology（Natural Science Edition），2022，50（2）：93-101.
5	夏毅敏，骆亮霖，郭堃，等．液压系统压力-速度复合控制策略研究［J］．华南理工大学学报（自然科学版），2023，51（1）：31-40.
	XIA Yimin， LUO Lianglin， GUO Kun，et al ．Pressure-velocity compound control strategy of hydraulic system［J］．Journal of South China University of Technology （Natural Science Edition），2023，51（1）：31-40.
6	YAO J ．Model-based nonlinear control of hydraulic servo systems：challenges，developments and perspectives［J］．Frontiers of Mechanical Engineering，2017，13（2）：179-210.
7	WANG C， JI X， ZHANG Z，et al ．Tracking differentiator based back-stepping control for valve-controlled hydraulic actuator system［J］．ISA Transactions，2022，119：208-220.
8	GUO Q， ZHANG Y， CELLER B G，et al ．Backstepping control of electro-hydraulic system based on extended-state-observer with plant dynamics largely unknown［J］．IEEE Transactions on Industrial Electronics，2016，63（11）：6909-6920.
9	GUO Q， ZUO Z， DING Z ．Parametric adaptive control of single-rod electrohydraulic system with block-strict-feedback model［J］．Automatica，2020，113：108807/1-9.
10	GUO Y， CHENG W， GONG D，et al ．Adaptively robust rotary speed control of an anchor-hole driller under varied surrounding rock environments［J］．Control Engineering Practice，2019，86：24-36.
11	YIN X， ZHANG W C， JIANG Z S，et al ．Adaptive robust integral sliding mode pitch angle control of an electro-hydraulic servo pitch system for wind turbine［J］．Mechanical Systems and Signal Processing，2019，133：105704/1-15.
12	YAO J， DENG W ．Active disturbance rejection adaptive control of hydraulic servo systems［J］．IEEE Transactions on Industrial Electronics，2017，64（10）：8023-8032.
13	ZHANG X， SHI G ．Dual extended state observer-based adaptive dynamic surface control for a hydraulic manipulator with actuator dynamics［J］．Mechanism and Machine Theory，2022，169：104647/1-15.
14	WRAT G， BHOLA M， RANJAN P，et al ．Energy saving and fuzzy-PID position control of electro-hydraulic system by leakage compensation through proportional flow control valve［J］．ISA Transactions，2020，101：269-280.
15	SHEN W， WANG J， HUANG H，et al ．Fuzzy sliding mode control with state estimation for velocity control system of hydraulic cylinder using a new hydraulic transformer［J］．European Journal of Control，2019，48：104-114.
16	YANG Y， LI Y， LIU X，et al ．Adaptive neural network control for a hydraulic knee exoskeleton with valve deadband and output constraint based on nonlinear disturbance observer［J］．Neurocomputing，2022，473：14-23.
17	GUO Q， CHEN Z ．Neural adaptive control of single-rod electrohydraulic system with lumped uncertainty［J］．Mechanical Systems and Signal Processing，2021，146：106869/1-17.
18	吉鑫浩，汪成文，陈帅，等．阀控电液位置伺服系统滑模反步控制方法［J］．中南大学学报（自然科学版），2020，51（6）：1518-1525.
	JI Xinhao， WANG Chengwen， CHEN Shuai，et al ．Sliding mode back-stepping control method for valve-controlled electro-hydraulic position servo system［J］．Journal of Central South University （Science and Technology），2020，51（6）：1518-1525.
19	GUO X， WANG H， HE X，et al ．Order-reduced-model based integral sliding mode control of a heavy-duty hydraulic manipulator with disturbances estimation ［J］．Proceedings of the Institution of Mechanical Engineers，Part I：Journal of Systems and Control Engineering，2022，236（4）：707-717.
20	DU H， SHI J， CHEN J，et al ．High-gain observer-based integral sliding mode tracking control for heavy vehicle electro-hydraulic servo steering systems［J］．Mechatronics，2021，74：102484/1-15.
21	DANG X， ZHAO X， DANG C，et al ．Incomplete differentiation-based improved adaptive backstepping integral sliding mode control for position control of hydraulic system［J］．ISA Transactions，2021，109：199-217.
22	BAKHSHANDE F， BACH R， SÖFFKER D ．Robust control of a hydraulic cylinder using an observer-based sliding mode control：theoretical development and experimental validation［J］．Control Engineering Practice，2020，95：104272/1-11.
23	王立新，赵丁选，刘福才，等．一类轻载电液位置伺服系统线性自抗扰控制［J］．控制理论与应用，2021，38（4）：503-515.
	WANG Lixin， ZHAO Dingxuan， LIU Fucai，et al ．Linear active disturbance rejection control for a class of electro-hydraulic position servo system with light load ［J］．Control Theory & Applications，2021，38（4）：503-515.
24	WANG C， QUAN L， ZHANG S，et al ．Reduced-order model based active disturbance rejection control of hydraulic servo system with singular value perturbation theory［J］．ISA Transactions，2017，67：455-465.

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