Application of PSO and TLBO algorithms with neural network for optimal design of electrical machines. Issue 2 (5th March 2018)

• Record Type: Journal Article
• Authors: Kheireddine, Bourahla; Zoubida, Belli; Tarik, Hacib; Imed, Achoui
• Is Part Of: Compel. Volume 37:Issue 2(2018)
• Page Start: 549
• Page End: 564
• Publication Date: 2018-03-05
• Subjects: Optimization -- Particle swarm optimization -- Artificial neural network -- Electrical machines -- Finite elements analysis -- Teaching–Learning-based optimization; Electrical engineering -- Data Processing -- Periodicals; Electrical engineering -- Mathematics -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Data Processing -- Periodicals; Electronics -- Mathematics -- Periodicals; 621.3
• DOI: 10.1108/COMPEL-12-2016-0532
• Languages: English
• ISSNs: 0332-1649

Abstract

Abstract : Purpose: This study aims to focus on the application of the stochastic algorithms for optimal design of electrical machines. Among them, the authors are interested in particle swarm optimization and teaching–learning-based optimization. Design/methodology/approach: The optimization process is realized by the coupling of the above methods to finite element analysis of the electromagnetic field. Findings: To improve the performance of these algorithms and reduce their computation time, a coupling with the artificial neuron network has been realized. Originality/value: The proposed strategy is applied to solve two optimization problems: Team workshop problem 25 and switched reluctance motor with flux barriers.