Event Triggered Adaptive Robust Trajectory Tracking Control for Multi-joint Manipulators

被引：0
|
作者：
Qian Q. [1 ]
Zhang A. [1 ]
Sun Y. [1 ]
机构：
[1] School of Mechanical and Automobile Engineering, Shanghai University of Engineering Science, Shanghai
来源：
Binggong Xuebao/Acta Armamentarii | 2019年 / 40卷 / 08期
关键词：
Event-based control; Multi-joint manipulator; Robust adaptive; Semi-global uniform ultimate boundedness; Trajectory tracking;
D O I：
10.3969/j.issn.1000-1093.2019.08.024
中图分类号：
学科分类号：
摘要：
For the multi-joint manipulator trajectory tracking control with uncertain disturbances and modelling errors, an event triggered controller is proposed based on adaptive robust control algorithm. The adaptive robust control algorithm is presented to ensure the trajectory tracking precision of multi-joint manipulator, and the adaptive term is used to deal with the uncertainty caused by uncertain disturbances and modelling errors. In the event triggered control framework, the current tracking errors and expected states are taken as inputs to define the state variables of event triggered control system, and Lyapunov stability theory is used to obtain the triggering condition,and no Zeno behaviours occur in the system. The control command is updated only when the triggering condition is satisfied, which can reduce the frequency of communication and computation, and improve the reliability. The semi-global uniform ultimate boundedness of multi-joint manipulator tracking control system is ensured, and the theoretical results are verified through simulation. © 2019, Editorial Board of Acta Armamentarii. All right reserved.
引用
收藏
页码：1732 / 1739
页数：7
相关论文
共 20 条
  • [1] Xin Y., Gao W.B., Research on adaptive control of robot and mechanical system, Robot, 2, (1990)
  • [2] Lin F., Brandt R.D., An optimal control approach to robust control of robot manipulators, IEEE Transactions on Robotics & Automation, 14, 1, pp. 69-77, (1998)
  • [3] Yu Z.G., Shen Y.L., Song Z.M., Robust adaptive motion control for manipulators, Control Theory and Applications, 28, 7, pp. 1021-1024, (2011)
  • [4] Jie C., Wei M., Sliding mode control for delayed T-S fuzzy neural network with norm-bounded uncertainties, Proceedings of International Conference on Mechanical Engineering and Control Systems, pp. 302-307, (2016)
  • [5] Tarn T.J., Ganguly S., Ramadorai A.K., Et al., Experimental evaluation of the nonlinear feedback robot controller, Proceedings of IEEE International Conference on Robotics and Automation, pp. 1638-1644, (1991)
  • [6] Simon D., Castaneda E.C., Freedman P., Design and analysis of synchronization for real-time closed-loop control in robotics, IEEE Transactions on Control Systems Technology, 6, 4, pp. 445-461, (1998)
  • [7] Tallapragada P., Chopra N., On event triggered trajectory tracking for control affine nonlinear systems, Proceedings of IEEE Conference on Decision and Control and European Control Conference, pp. 5377-5382, (2011)
  • [8] Tallapragada P., Chopra N., On event triggered tracking for nonlinear systems, IEEE Transactions on Automatic Control, 58, 9, pp. 2343-2348, (2013)
  • [9] Kamboj A., Dhar N.K., Verma N.K., Event-triggered control for trajectory tracking by robotic manipulator, Advances in Intelligent Systems and Computing, 798, pp. 161-170, (2019)
  • [10] Lehmann D., Lunze J., Extension and experimental evaluation of an event-based state-feedback approach, Control Engineering Practice, 19, 2, pp. 101-112, (2011)
12