Adaptive Discrete-Time Quantized Control for Multi-machine Power System with SVC

被引：0

作者：

Li, Yan ^{[1
]}

Yuan, Xuezhu ^{[2
]}

Tian, Bing ^{[2
]}

Yuan, Rong ^{[1
]}

Xu, Nan ^{[3
]}

Zhu, Guoqiang ^{[2
]}

机构：

[1] Chongqing Elect Power Coll, Coll Elect Engn, Chongqing, Peoples R China

[2] Northeast Elect Power Univ, Sch Automat Engn, Jilin, Jilin, Peoples R China

[3] Southeast Univ, Sch Automat, Nanjing, Peoples R China

来源：

2024 5TH INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND APPLICATION, ICCEA 2024 | 2024年

关键词：

Multi-machine power system; Discrete time; RBF neural network; Adaptive dynamic surface; Hysteresis quantizer;

D O I：

10.1109/ICCEA62105.2024.10603847

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, a discrete-time adaptive dynamic surface quantization control method has been proposed for a class of multi-machine power systems with Static Var Compensator (SVC). The strategy combines RBF neural network and discrete low-pass filter to solve the differential explosion problem in backstepping and simplify the control law. Chatter is also reduced by a modified hysteresis quantizer, and digital control is achieved. Ultimate uniformly bounded properties of closed-loop systems are proved by designing Lyapunov functions and the simulation results confirm the effectiveness of the method.

引用

页码：1757 / 1761

页数：5

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