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
相关论文
共 50 条
  • [41] Stabilization control of multi-machine power systems by adaptive power system stabilizer using frequency domain analysis
    Senjyu, T., 1600, John Wiley and Sons Inc. (142):
  • [42] Stabilization control of multi-machine power systems by adaptive power system stabilizer using frequency domain analysis
    Senjyu, T
    Yamashita, T
    Uezato, K
    ELECTRICAL ENGINEERING IN JAPAN, 2003, 142 (02) : 10 - 20
  • [43] Improving Transient Stability with Multi-objective Allocation and Parameter Setting of SVC in a Multi-machine Power System
    Gitizadeh, Mohsen
    Ghavidel, Sahand
    IETE JOURNAL OF RESEARCH, 2014, 60 (01) : 33 - 41
  • [44] Theory and method for parametric adaptive control design of multi-machine power systems
    Wang, Jie
    Chen, Chen
    Wu, Hua
    Su, Jian-She
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2002, 22 (05): : 5 - 9
  • [45] Quantized control for polynomial fuzzy discrete-time systems
    Zhou, Qi
    Chen, Ziran
    Li, Xinchen
    Gao, Yabin
    COMPLEXITY, 2015, 21 (02) : 325 - 332
  • [46] Quantized Control of Nonlinear Quadratic Discrete-Time Systems
    Maestrelli, Rafael
    Coutinho, Daniel
    de Souza, Carlos E.
    Xie, Lihua
    2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC), 2016, : 4843 - 4848
  • [47] Quantized Feedback Control for Discrete-time Singular Systems
    Shen, Jiawei
    Lin, Jinxing
    Xiao, Min
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 1303 - 1308
  • [48] Nonlinear Adaptive L2-Gain Decentralized Excitation Control for Multi-Machine Power System
    Gu Z.
    Sun X.
    Yu Z.
    Zhu C.
    Gu, Zhifeng (gzfgohappy@163.com), 2018, Power System Technology Press (42): : 3355 - 3360
  • [49] Transient Stability Analysis of Multi-machine Power System and First Swing Stability Analysis using SVC
    Sebastian, Betsy
    Garg, Rachana
    2014 INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE), 2014,
  • [50] Adaptive Rule-base Fuzzy Power System Stabilizer For a Multi-machine System
    Hussein, T.
    Shamekh, A.
    2013 21ST MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED), 2013, : 1514 - 1519
12345