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Hybrid membrane computing and pigeon-inspired optimization algorithm for brushless direct current motor parameter design

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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 with better searching efficiency. Comparative simulations are conducted, and comparative results are given to show the feasibility and effectiveness of our proposed hybrid algorithm for high nonlinear optimization problems.

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Authors and Affiliations

  1. Bio-inspired Autonomous Flight Systems (BAFS) Research Group, Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing, 100191, China

    YiMin Deng, WeiRen Zhu & HaiBin Duan

  2. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    YiMin Deng, WeiRen Zhu & HaiBin Duan

Authors
  1. YiMin Deng
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  2. WeiRen Zhu
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  3. HaiBin Duan
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Correspondence to HaiBin Duan.

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Deng, Y., Zhu, W. & Duan, H. Hybrid membrane computing and pigeon-inspired optimization algorithm for brushless direct current motor parameter design. Sci. China Technol. Sci. 59, 1435–1441 (2016). https://doi.org/10.1007/s11431-016-6048-8

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  • DOI: https://doi.org/10.1007/s11431-016-6048-8

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