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

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 (D...

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Vydáno v:2011 Power Engineering and Automation Conference Ročník 3; s. 183 - 186
Hlavní autoři: Huynh, D. C., Dinh, B. H., Dunnigan, M. W., Nguyen, T. A. T., Le, N. H.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.09.2011
Témata:
Convergence
Heuristic algorithms
Induction machines
Optimization
Parameter estimation
Particle swarm optimization
particle swarm optimization algorithm
Windings
ISBN:9781424496914, 1424496918
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Shrnutí: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.
ISBN:9781424496914
1424496918
DOI:10.1109/PEAM.2011.6135102