Predictor-Based Iterative Neural Dynamic Surface Control for Three-Phase Voltage Source PWM Rectifier

被引：2

作者：

Diao, Liang ^{[1
]}

Wang, Dan ^{[1
]}

Peng, Zhouhua ^{[1
]}

Guo, Lei ^{[1
]}

机构：

[1] Dalian Maritime Univ, Sch Marine Engn, Dalian 116026, Peoples R China

来源：

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING | 2017年 / 12卷 / 06期

基金：

中国博士后科学基金; 中国国家自然科学基金;

关键词：

pulse width modulation rectifier; neural network; predictor; iterative update law; finite-time-convergent differentiator; UNCERTAIN NONLINEAR-SYSTEMS; FINITE-TIME STABILIZATION; DIRECT POWER-CONTROL; GRID-SIDE CONVERTER; ADAPTIVE-CONTROL; SLIDING MODE; DISTURBANCE; DESIGN; SCHEME;

D O I：

10.1002/tee.22486

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper addresses the control problem of a three-phase voltage source pulse width modulation rectifier in the presence of parametric uncertainties and external time-varying disturbances. An adaptive controller is designed by combining a modified dynamic surface control method and a predictor-based iterative neural network control algorithm. Especially, neural networks with iterative update laws based on prediction errors are employed to identify the lumped uncertainties. Besides, a finite-time-convergent differentiator, instead of a first-order filter, is used to obtain the time derivative of the virtual control law. Using a Lyapunov-Krasovskii functional, it is proved that all signals in the closed-loop system are ultimately uniformly bounded. Both simulation and experimental studies are provided to show the effectiveness of the proposed approach. (C) 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

引用

页码：942 / 951

页数：10

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