Adaptive Dynamic Surface Control of a Flexible Robot Based on the K-State Observer

被引：0

作者：

Yang L. ^{[1
]}

Tang C. ^{[1
]}

Yang J. ^{[2
,3
,4
]}

Liu F. ^{[5
]}

Li T. ^{[6
]}

机构：

[1] Nanyang Institute of Technology, Nanyang, 473000, Henan

[2] General Graduate School of Dongseo University, Busan

[3] Henan Institute of Technology, Xinxiang, 453000, Henan

[4] Henan Key Equipment Engineering, Research Center for New Energy Power Generation, Xinxiang, 453000, Henan

[5] Xiangyang public inspection and Testing Center, Xinxiang, 441100, Henan

[6] Department of Informatics, University of Zurich, Zurich

来源：

Tang, Chuansheng (cs111@163.com) | 1600年 / Eastern Macedonia and Thrace Institute of Technology卷 / 13期

关键词：

Adaptive estimation; Dynamic surface control; Flexible joint robot; Inverse control; K-state observer;

D O I：

10.25103/jestr.136.23

中图分类号：

学科分类号：

摘要：

The flexible manipulator is a complex electromechanical nonlinear system with a rigid flexible coupling, and its control performance is affected by many factors, such as inaccurate modelling and measurement, load variation, and uncertainty of external disturbance. In view of improving the effect of time-varying model parameters and external disturbances on the performance of the control system, an adaptive dynamic surface control method of the flexible manipulator based on K-state observer was proposed in this study. On the basis of the analysed characteristics of the flexible manipulator system model, a K-state observer had been constructed when the system state was not completely measurable. Then, an adaptive dynamic surface control method was designed by taking the position and speed of the flexible manipulator as the control objective. Finally, the effectiveness of the control method was verified by simulation. Results show that, when no model parameter uncertainty exists in the system, the dynamic surface control has a higher tracking accuracy than the inversion control, the maximum tracking error of angular velocity is reduced by 1.3 times, and the steady-state control input is reduced by 550 times. When the system has model parameters but only the joint angle position can be measured, the conventional inversion control and dynamic surface control cannot achieve system control. The adaptive dynamic surface control can achieve high-precision system tracking at 2.5 s, and the state and parameter estimation of the system can achieve online observation at 4 s and 2.5 s, respectively; and the adaptive dynamic surface control in the steady-state control input can reach 1/18. The proposed method can provide a reference for a flexible robot to achieve high-precision tracking in a complex assembly environment. © 2020 School of Science, IHU

引用

页码：166 / 174

页数：8

共 26 条

[1]

Zhou Y. P., Lou J. Q., Chen T. H., Ma J. Q., Wei Y. D., Coupling dynamic modeling of a flexible manipulator driven by servo joint and test recognition, Journal of Vibration and Shock, 38, 9, pp. 277-284, (2019)

[2]

Lei R. H., Chen L., Adaptive neural network fault-tolerant control and residual vibration suppression for flexible-arm space robot with attitude-controlled base, Journal of Vibration and Shock, 39, 7, pp. 156-162, (2020)

[3]

Du X. L., Du J. L., Bao H., Zhong W., Cui K., Dynamic analysis of deployable antennas considering truss flexibility, Journal of Mechanical Engineering, 56, 7, pp. 119-126, (2020)

[4]

Guo Y. N., Wang P. Y., Jin S., A new optimization approach to the flexible spacecraft actuators placement, Flight Control and Detection, 2, 5, pp. 49-54, (2019)

[5]

Duan H. F, Han W., Jiang L. Z., Chen Y. S., Design of flexible assembly automation system for socket switch based on industrial robot, Manufacturing Technology and Machine Tool, 3, pp. 13-16, (2020)

[6]

Meng F. G., Wang W., Li X. P., Liu Y. P., A robot off-line programming system for typical space line cutting, Machinery Design and Manufacture, 9, pp. 236-239, (2019)

[7]

Tu Q., Yue D. H., Wang Y.J., Liu G. X., Design and investigation on the deformation characteristics of soft robot hands for lateral grasping of fruit and vegetables, Machine Tool and Hydraulics, 47, 9, pp. 51-57, (2019)

[8]

Feng Y. B., Zhao X. H., He Z., Li Z. G, Wang Y. B., Depth hover control of spherical robot for internal detection of oil-immersed transformer, Control and Decision, 35, 2, pp. 375-381, (2020)

[9]

Huang X. R., Song Y. Y., Li Q. S., Xiao X., A vibration suppression algorithm for industrial robot joint servo system based on internal model control, Transactions of China Electrotechnical Society, 34, 3, pp. 497-505, (2019)

[10]

Liu L. Y., Design and application of internal model control for jointed cloud robot with delay time, Journal of Shijiazhuang University of Applied Technology, 31, 4, pp. 8-12, (2019)

← 1 2 3 →