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Comparison between GA-based LQR and conventional LQR control method of DFIG wind energy system

Authors: Ravi Bhushan; Kalyan Chatterjee; Ravi Shankar 0004;

Comparison between GA-based LQR and conventional LQR control method of DFIG wind energy system

Abstract

This work addresses an application of genetic algorithm (GA) methodology in doubly-fed induction generator (DFIG) systems to optimize the weighting matrices of the linear quadratic regulator (LQR). The GA-based LQR control technique will elude the trial-and-error approach in constructing the appropriate weighting matrices. The proposed controller is compared with the conventional LQR control method for the stator terminal voltage perturbations. The stability and the dynamic responses of the studied system are examined through eigenvalues and the time response analysis. Simulation results demonstrate that the GA-based LQR control methodology is more stable and robust than in comparison to the conventional LQR control method.

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
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