An adaptive optimization method using Kriging model and Latin hypercube design and its application to optimum design of PMLSM

Author

Zhang, Yanli ; Yan, Bing ; Xie, Dexin ; Koh, Chang Seop

Author_Institution

Sch. of Electr. Eng., Shenyang Univ. of Technol., Shenyang, China

fYear

2010

fDate

9-12 May 2010

Firstpage

1

Lastpage

1

Abstract

This paper presents a computationally efficient optimal design algorithm for electromagnetic devices by combining Kriging interpolation approximation of the objective function and genetic algorithm. In this method, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design (LHD). The proposed algorithm is applied to the optimum design of permanent magnet linear synchronous motor (PMLSM) and the computational efficiency is investigated.

Keywords

Pareto optimisation; electromagnetic devices; linear synchronous motors; permanent magnet motors; statistical analysis; Kriging interpolation approximation; Latin hypercube design; PMLSM; Pareto-optimal sampling points; adaptive optimization method; computational efficiency; electromagnetic devices; genetic algorithm; permanent magnet linear synchronous motor; Algorithm design and analysis; Approximation algorithms; Design methodology; Electromagnetic devices; Genetic algorithms; Hypercubes; Interpolation; Optimization methods; Sampling methods; Synchronous motors;

fLanguage

English

Publisher

ieee

Conference_Titel

Electromagnetic Field Computation (CEFC), 2010 14th Biennial IEEE Conference on

Conference_Location

Chicago, IL

Print_ISBN

978-1-4244-7059-4

Type

conf

DOI

10.1109/CEFC.2010.5481388

Filename

5481388