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Parameter estimation of a single-phase induction machine using a dynamic particle swarm optimization algorithm

Authors: Duy C. Huynh; Bach H. Dinh; Matthew W. Dunnigan; Thu A. T. Nguyen; Nam H. Le;

Parameter estimation of a single-phase induction machine using a dynamic particle swarm optimization algorithm

Abstract

This paper proposes a new parameter estimation approach for a single-phase induction machine (SPIM) whose parameters are usually obtained using several traditional techniques such as the DC, no-load, load and locked-rotor tests. The proposal is based on using a dynamic particle swarm optimization (Dynamic PSO) algorithm. The dynamic PSO algorithm modifies the algorithm parameters to improve the performance of the standard PSO algorithm. The algorithms use the experimental measurements of the currents and active powers in the SPIM main and auxiliary windings as the inputs to the parameter estimator. The experimental results obtained compare the estimated SPIM parameters with the SPIM parameters achieved using the traditional tests. There is also a comparison of the solution quality between the standard PSO and dynamic PSO algorithms. The results show that the dynamic PSO algorithm is better than the standard PSO algorithm for parameter estimation of the SPIM.

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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!
1
Average
Average
Average
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