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
收藏
页码：1757 / 1761
页数：5
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