Adaptive Sliding Mode Control for a Class of Manipulator Systems with Output Constraint

被引:2
作者
Li, Guangshi [1 ]
机构
[1] Anshan Normal Univ, Comp Ctr, Anshan 114016, Peoples R China
关键词
NONLINEAR-SYSTEMS; STATE CONSTRAINTS; FEEDBACK-SYSTEMS; TRACKING CONTROL; NEURAL-NETWORK; PID CONTROL; DESIGN;
D O I
10.1155/2021/6642795
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this paper, an adaptive sliding mode control method based on neural networks is presented for a class of manipulator systems. The main characteristic of the discussed system is that the output variable is required to keep within a constraint set. In order to ensure that the system output meets the time-varying constraint condition, the asymmetric barrier Lyapunov function is selected in the design process. According to Lyapunov stability theory, the stability of the closed-loop system is analyzed. It is demonstrated that all signals in the resulted system are bounded, the tracking error converges to a small compact set, and the system output limits in its constrained set. Finally, the simulation example is used to show the effectiveness of the presented control strategy.
引用
收藏
页数:7
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