2016
DOI: 10.1007/s11431-016-6048-8
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Hybrid membrane computing and pigeon-inspired optimization algorithm for brushless direct current motor parameter design

Abstract: In this paper, a novel approach is proposed for solving the parameter design problem of brushless direct current (BLDC) motor, which is based on the membrane computing (MC) and pigeon-inspired optimization (PIO) algorithm. The motor parameter design problem is converted to an optimization problem with five design parameters and six constraints. The PIO algorithm is introduced into the framework of MC for improving the global convergence performance. The hybrid algorithm can improve the population diversity wit… Show more

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Cited by 8 publications
(3 citation statements)
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“…The researchers demonstrated that the performance of the PPPIO technique outperformed both the PIOA and particle swarm optimization (PSO) algorithms. Deng et al [49] integrated the PIOA with membrane computing to address the parameter design challenges encountered in an industrial motor.…”
Section: Literature Review On Pigeon-inspired Optimization Algorithm ...mentioning
confidence: 99%
“…The researchers demonstrated that the performance of the PPPIO technique outperformed both the PIOA and particle swarm optimization (PSO) algorithms. Deng et al [49] integrated the PIOA with membrane computing to address the parameter design challenges encountered in an industrial motor.…”
Section: Literature Review On Pigeon-inspired Optimization Algorithm ...mentioning
confidence: 99%
“…To improve the performance of basic PIO, Chen and Duan [24] introduced multi-scale Gaussian mutation PIO (MGMPIO) by applying a multi-scale Gaussian operation to all positions and the global best position X g in the map and compass operator. Inspired by the membrane computing model, Deng et al [44] put forward hybrid membrane computingbased PIO (HMCPIO) by adding a communication operator after the landmark operator. Duan and Wang [45] applied an orthogonal design strategy to the initialization of PIO, and called the novel algorithm with a rich population diversity orthogonal PIO (OPIO).…”
Section: Variants Of Pigeon-inspired Optimizationmentioning
confidence: 99%
“…The PIO algorithm has been widely applied in many areas such as biomedical engineering [2], electrical engineering [3,4], trajectory optimization [5], and optimal control design problems [6]. It has been proven to be effective for solving parametric design problems.…”
Section: Introductionmentioning
confidence: 99%