Adaptive sliding mode control based on ultra-local model for robotic manipulator

被引：0
|
作者：
Wu A.-G. [1 ]
Han J.-Q. [1 ]
Dong N. [1 ]
机构：
[1] School of Electrical and Information Engineering, Tianjin University, Tianjin
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2020年 / 50卷 / 05期
关键词：
Automatic control technology; Finite time convergence; Neural network; Robotic manipulator; Sliding mode control; Trajectory tracking; Ultra-local mode;
D O I：
10.13229/j.cnki.jdxbgxb20190489
中图分类号：
学科分类号：
摘要：
A model-free control method is proposed for trajectory tracking of multi-degree of freedom robotic manipulator to deal with the problems of relying too much on the precise mathematical model and low tracking accuracy. This method combines the adaptive neural network, the ultra-local model and the integral terminal sliding mode. First, an ultra-local model based on delay estimation is used to approximate the dynamic model of the manipulator. Then, a neural network is used to compensate the errors of delay estimation because of its nonlinear approximation capability. Finally, an integral sliding mode controller is designed for the ultra-local model to improve the convergence speed and control accuracy of the system and realize the high-precision trajectory tracking of the manipulator without relying on the dynamic model. The stability and finite time convergence of closed loop system are proved by Lyapunov theory. Experimental results show that the proposed control method can realize the high precision tracking control of the manipulator without depending on the model information completely. © 2020, Jilin University Press. All right reserved.
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页码：1905 / 1912
页数：7
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