Proceedings ArticleDOI
Parameter identification of induction motors using differential evolution
R.K. Ursem,P. Vadstrup +1 more
- Vol. 2, pp 790-796
TLDR
The differential evolution algorithm is applied to parameter identification of two induction motors used in the house circulation pumps produced by the Danish pump manufacturer Grundfos A/S and outperformed the previously best known algorithms on both problems.Abstract:
Parameter identification of system models is a fundamental step in the process of designing a controller for a system. In control engineering, a wide selection of analytic identification techniques exists for linear systems, but not for nonlinear systems. Instead, the model parameters may be determined by an optimization algorithm by minimizing the error between model output and measured data. We apply the differential evolution algorithm to parameter identification of two induction motors. The motors are used in the house circulation pumps produced by the Danish pump manufacturer Grundfos A/S. The experiments presented use differential evolution, and is a follow-up study of an comparison of eight stochastic search algorithms on the two motor identification problems. In conclusion, the differential evolution algorithm outperformed the previously best known algorithms on both problems.read more
Citations
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MolDock: a new technique for high-accuracy molecular docking.
TL;DR: The docking scoring function of MolDock is an extension of the piecewise linear potential including new hydrogen bonding and electrostatic terms, which identifies the most promising docking solution from the solutions obtained by the docking algorithm.
Proceedings ArticleDOI
A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems
J.S. Vesterstrom,René Thomsen +1 more
TL;DR: The results from this study show that DE generally outperforms the other algorithms, however, on two noisy functions, both DE and PSO were outperformed by the EA.
Proceedings ArticleDOI
Multimodal optimization using crowding-based differential evolution
TL;DR: The introduced CrowdingDE algorithm is compared with a DE using the well-known sharing scheme that penalizes similar candidate solutions and outperformed the sharing-based DE algorithm on fourteen commonly used benchmark problems.
Journal ArticleDOI
Differential evolution and particle swarm optimisation in partitional clustering
Sandra Paterlini,Thiemo Krink +1 more
TL;DR: The empirical results show that DE is clearly and consistently superior compared to GAs and PSO for hard clustering problems, both with respect to precision as well as robustness (reproducibility) of the results.
Journal ArticleDOI
Influence of crossover on the behavior of Differential Evolution Algorithms
TL;DR: This work aims to analyze the impact the crossover operator and its parameter, the crossover rate, has on the behavior of Differential Evolution and illustrates the difference between binomial and exponential crossover variants.
References
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Journal ArticleDOI
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Rainer Storn,Kenneth Price +1 more
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Diversity-Guided Evolutionary Algorithms
TL;DR: The diversity-guided evolutionary algorithm (DGEA) uses the well-known distance-to-average-point measure to alternate between phases of exploration (mutation) and phases of exploitation (recombination and selection).
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