Fuzzy Position Control of PMBLDC Motor using Adaptive Genetic Algorithm

B  S  Sathish   and P  Thirusakthimurugan

doi:10.17485/ijst/2015/v8iS8/71713

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Fuzzy Position Control of PMBLDC Motor using Adaptive Genetic Algorithm

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8iS8/71713

Year: 2015, Volume: 8, Issue: Supplementary 8, Pages: 1-7

Original Article

Fuzzy Position Control of PMBLDC Motor using Adaptive Genetic Algorithm

B. S. Sathish^1* and P. Thirusakthimurugan²

¹Sathyabama University, Chennai, Tamilnadu, India; [email protected]
²Department of EIE, Pondicherry Engineering College, Pondicherry-14, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

In this paper, an identification of position controller design for Permanent Magnet Brushless DC Motor (PMBLDCM) using Fuzzy Adaptive Genetic Algorithm (FAGA) is presented. For optimal searching of the scaling factors of the antecedent and consequent parameters of the T-S fuzzy model is identified to minimize the Integral square error (ISE) between the closed-loop outputs of the motor system and the Fuzzy T-S model. An interesting alternative that could be investigated the use of fuzzy logic control methods.The mechanism of designing and implementation of transfer system (T.S).model FLC based on AGA is described and the simulation results are obtained using the proposed technique in comparison with the conventional PI controller is prescribed. The simulation result shows that the identification using the Adaptive genetic Algorithm based Fuzzy transfer system (T.S) model has smaller error when compared to the transfer function (T.F) model.
Keywords: Adaptive Genetic Algorithm, Fuzzy Adaptive Genetic Algorithm, Integral Square Error, Permanent Magnet Brushless DC Motor, Position Controller