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An H_2 optimal adaptive power sytem stabilizer

A. Soos
- 01 Jan 2002 - 
- Vol. 17, Iss: 1, pp 143-149
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This article is published in IEEE Transactions on Energy Conversion.The article was published on 2002-01-01 and is currently open access. It has received 18 citations till now.

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Journal ArticleDOI

Design of a nonlinear power system stabilizer using synergetic control theory

TL;DR: In this article, a nonlinear power system stabilizer based on synergetic control theory is proposed to provide damping torque for the synchronous generators to suppress the oscillations by generating supplementary control signals for the generator excitation system.
Journal ArticleDOI

Design of an adaptive neural network based power system stabilizer

TL;DR: An indirect adaptive neural network based power system stabilizer (IDNC) design that consists of a neuro-controller, which is used to generate a supplementary control signal to the excitation system, and a Neuro-identifier, used to model the dynamics of the power system and to adapt the neuro- controller parameters.
Journal ArticleDOI

Parameter tuning of power system stabilizer using eigenvalue sensitivity

TL;DR: In this article, the authors proposed a method for tuning PSS parameter tuning based on the eigenvalue sensitivity analysis of changes of PSS parameters, which can be applied on-line so the PSS structure and settings can be adaptive.
Journal ArticleDOI

Enhancement of power system dynamic performance through an on-line self-tuning adaptive SVC controller

TL;DR: In this paper, a self-tuning adaptive control algorithm was used as a supplementary controller for the static VAr compensators (SVC) for voltage control of long distance bulk power transmission lines.
Proceedings ArticleDOI

Decentralized sliding mode control technique based power system stabilizer (PSS) for multimachine power system

TL;DR: The design of PSS for multimachine power system (MMPS) using output feedback sliding mode control is proposed, which does not require the complete states of the system for feedback and is easily implementable.