Intelligent control of the Unified Power Flow Controller using a hybrid approach

被引：0

作者：

Zebirate, S. ^{[1
]}

Chaker, A. ^{[1
]}

Feliachi, A. ^{[2
]}

机构：

[1] SCAMBRE Laboratory, ENSET, BP 225 Bureau Zerbani Mohamed Es-Senia, 31 106, Oran, Algeria

[2] LDCSEE West Virginia University, P.O. Box 6109, Morgantown, WV 26506-6109, United States

来源：

Advances in Modelling and Analysis C | 2008年 / 63卷 / 3-4期

关键词：

Adaptive control systems - Flow control - Fuzzy neural networks - Computer circuits - Power control - State feedback - Controllers - Electric load flow - Fuzzy inference - Model predictive control - Electric control equipment;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper presents two hybrid control architectures of a PWM based Unified Power Flow Controller (UPFC). The effectiveness of this compensator depends on the choice of the local control strategy. The proposed hybrid decoupling control scheme combines artificial neural networks and fuzzy logic with the classical control design methods. Fuzzy logic and neural network-based controllers are considered as potential candidates for such an application. In the first architecture, neural networks are used in an internal model control structure. In the second approach a fuzzy state feedback controller is developed based on the classical decoupling technique. The performance of such hybrid control systems and their ability to cope with disturbance and parameter variations are evaluated and compared with that of a Pi-Decoupled controller tuned by Ziegler and Nichols by an extensive simulation analysis.

引用

页码：44 / 62