NDLI: Robust neural network-based control of static var compensator

Content Provider	IET Digital Library
Author	Chang, Yeong Chan
Abstract	This study addresses the problem of designing robust stabilisation control for a large class of uncertain single-machine infinite-bus electrical power systems with static var compensator (SVC). This class of systems may be perturbed by plant uncertainties, unmodelled perturbations and external disturbances. An adaptive neural network-based dynamic feedback controller is developed such that all the states and signals of the closed-loop system are bounded and the stabilisation error can be made as small as possible. As the small perturbations in the input weighting gains are neglected, an H∞ control performance can be guaranteed. The adaptive neural network approximation systems are designed to learn the behaviours of the unknown functions, and in turn a modified procedure is proposed such that the number of the neural network basis functions can be significantly reduced. Consequently, the intelligent robust control scheme developed here possesses the properties of computational simplicity and easy implementation from the viewpoint of practical applications. The developed robust control scheme not only can handle a large class of uncertain SVC-driven power systems, but also achieve the aim of enhancing the stability performance. Finally, simulations are provided to demonstrate the effectiveness and performance of the proposed control algorithm.
Starting Page	1964
Ending Page	1977
Page Count	14
ISSN	17554535
Volume Number	7
e-ISSN	17554543
Issue Number	Issue 8, Aug (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-pel/7/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-pel.2013.0650
Journal	IET Power Electronics
Publisher Date	2014-06-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Control Adaptive Neural Network-based Dynamic Feedback Controller Closed Loop System Closed-loop System Computational Simplicity Control of Electric Power System Control System Analysis Control System Synthesis Feedback Hâˆž Control Hâˆž Control Performance Intelligent Control Scheme Neurocontrol Neurocontrollers Optimal Control Other Power Apparatus And Electric Machine Power System Control Robust Control Robust Neural Network-based Control Self Adjusting Control System Stabilisation Control Design Stability in Control Theory Static Var Compensator Static VAr Compensators SVC-driven Power System Synthesis Method Uncertain Single-machine Infinite-bus Electrical Power System
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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