Robust adaptive finite-time tracking control of uncertain mechanical systems with input saturation and deadzone

被引:9
|
作者
Wang, Baofang [1 ]
Li, Sheng [1 ]
Chen, Qingwei [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Finite-time control; adaptive control; mechanical systems; input saturation and deadzone; neural networks; EULER-LAGRANGE SYSTEMS; NONLINEAR-SYSTEMS; ROBOTIC MANIPULATORS; STABILIZATION; STABILITY; OBSERVERS;
D O I
10.1177/0142331218767490
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper addresses the problem of robust adaptive finite-time tracking control for a class of mechanical systems in the presence of model uncertainties, unknown external disturbances, and input nonlinearities containing saturation and deadzone. Without imposing any conditions on the model uncertainties, radial basis function neural networks are used to approximate unknown nonlinear continuous functions, and an adaptive tracking control scheme is proposed by exploiting the recursive design method. It is shown that the input saturation and deadzone model can be expressed as a simple linear system with a time-varying gain and bounded disturbance. An adaptive compensation term for the upper bound of the lumped disturbance is introduced. The semi-global finite-time uniform ultimate boundedness of the corresponding closed-loop tracking error system is proved with the help of the finite-time Lyapunov stability theory. Finally, an example is given to demonstrate the effectiveness of the proposed method.
引用
收藏
页码:560 / 572
页数:13
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