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Control strategy of excavator working device based on iterative sliding mode
Published:2022-06-16 author:LI Jie, WANG Xiao-wen, WANG Hao-qi, et al. Browse: 63 Check PDF documents
Control strategy of excavator working device 
based on iterative sliding mode


LI Jie1, WANG Xiao-wen1, WANG Hao-qi1, ZHANG Gui-xi2

(1.School of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;

2.JunzeHuitong Technology Development Co., Ltd., Beijing 100010, China)


Abstract: The excavator working device had the characteristics of complex, strong coupling, nonlinearity and time lag, and there was also the problem of load uncertainty in the working process, resulting in low working efficiency of the excavator and large mechanical wear. Aiming at the problem, a control strategy combining iterative learning control and sliding mode control was adopted to study the tracking control performance of each joint trajectory of the excavator working device. First of all, the dynamic model of the working device of the excavator was established by using the Lagrangian method of mechanics. Then, the control law was deduced and defined, and the stability of the controller was verified by the Lyapunov theory. Finally, an iterative sliding mode controller was designed. Using the mini Komatsu excavator PC02-1 as a platform, the variables required for trajectory control were determined, and the trajectory tracking performance of the excavator working device was numerically simulated by MATLAB. The research results show that this method can effectively improve the tracking speed and tracking accuracy of each joint of the excavator working device in the face of external disturbances, and weaken the chattering phenomenon of traditional sliding mode control to a certain extent. The uncertainty of the system has strong robustness, which verifies that the proposed control method has better control performance.

Key words:  hydraulic excavator; trajectory tracking; iterative learning control; sliding mode control; MATLAB
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