Adaptive Neural Control Design for Strict-Feedback Time-Delay Nonlinear Systems Based on Fast Finite-Time Stabilization: A Case Study of Synchronous Generator Systems

被引：0
|
作者：
Wang, Honghong [1 ]
Chen, Bing [2 ]
Lin, Chong [2 ]
Xu, Gang [3 ]
机构：
[1] Qingdao Univ, Coll Elect Engn, 308 Ningxia Rd, Qingdao 266071, Shandong, Peoples R China
[2] Qingdao Univ, Inst Complex Sci, 308 Ningxia Rd, Qingdao 266071, Shandong, Peoples R China
[3] Weifang Vocat Coll, Sch Mech & Elect Engn, 8029 Dongfeng East St, Weifang 261041, Shandong, Peoples R China
来源：
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2024年 / 28卷 / 06期
关键词：
practical finite-time stability; neural adaptive control; backstepping design; synchronous generator; excitation control; SLIDING-MODE CONTROL; TRACKING CONTROL; STABILITY; CONSENSUS;
D O I：
10.20965/jaciii.2024.p1231
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This study aims to investigate the finite-time control problem for a class of strict-feedback time-delay nonlinear systems with unknown functions. The control design is based on a fast finite-time practical stability criterion. Unknown nonlinear functions can be estimated using the universal approximation performance of neural networks. Finite-time control design is performed using adaptive backstepping technology. By performing closed-loop stability analyses and choosing appropriate Lyapunov-Krasovskii functionals, all signals in a closed-loop system can be bounded within a finite time. Subsequently, the proposed control method can be applied for the excitation control of synchronous generators. The effectiveness of the proposed method is verified using a numerical model of a single-machine power system.
引用
收藏
页码：1231 / 1239
页数：9
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