Time-varying Output Constraint for DC Motor Control

被引：0

作者：

Ma, Lei ^{[1
]}

Lu, ShuMin ^{[1
]}

Gong, MingZhe ^{[1
]}

Chen, Jie ^{[2
]}

Liu, YanJun ^{[1
]}

机构：

[1] Liaoning Univ Technol, Coll Sci, Jinzhou 121001, Liaoning, Peoples R China

[2] AHMS Inc, 4642-91 Ave, Edmonton, AB T6B 2L1, Canada

来源：

IEEE ICCSS 2016 - 2016 3RD INTERNATIONAL CONFERENCE ON INFORMATIVE AND CYBERNETICS FOR COMPUTATIONAL SOCIAL SYSTEMS (ICCSS) | 2016年

关键词：

Lyapunov Function; Uncertain nonlinear systems; Neural networks; Adaptive control; NONLINEAR-SYSTEMS; ADAPTIVE-CONTROL; TRACKING CONTROL; NEURAL-CONTROL; SYNCHRONIZATION;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a control problem for a class of DC motor nonlinear systems with output constraints, and the constraints are in time-varying form. Based on the dynamics system of the DC motor, a nonlinear model of the system with modeling uncertainties is established. Then an asymmetric time-varying Barrier Lyapunov Function (BLF) is proposed to guarantee the output to meet the constraints and the radial basis function neural networks (RBFNNs) are employed to approximate unknown function. By employing the backstepping method, the adaptive law based on DC motor nonlinear model is given. Then, all the signals in the closed-loop system are shown to be semi globally uniformly ultimately bounded,, the output constraint is satisfied, as well as the tracking error converges to a bounded compact set.

引用

页码：151 / 154

页数：4

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