The Multiobjective Optimal Design of a Two-Degree-of-Freedom Hybrid Magnetic Bearing

被引:7
|
作者
Liu, Xu [1 ,2 ]
Han, Bangcheng [1 ,2 ]
机构
[1] Fundamental Sci Novel Inertial Instrument & Nav S, Beijing 100191, Peoples R China
[2] Beihang Univ, Sch Instrument Sci & Optoelect Engn, Beijing 100191, Peoples R China
关键词
Chaos local search particle swarm optimization (CLSPSO); multiobjective optimization (MOO); penalty function; two-degree-of-freedom hybrid magnetic bearing (MB); utilization vector; PARTICLE SWARM OPTIMIZATION; INTEGRATED DESIGN; ALGORITHM;
D O I
10.1109/TMAG.2014.2313315
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The magnetic bearing's (MB) performance is determined by its electromagnetic and mechanical parameters, which should be optimized to meet the working requirements. Many optimal methods of MB have been only focused on a single objective, which may be limited to a small amount of aspects, while other important ones are ignored. A multiobjective optimization (MOO) model to design the MB considered for a better comprehensive property is proposed in this paper. After modeling the equivalent circuit model whose simplification has been clarified by finite element method, we provide the constraints and optimal objectives in the shape of analytical expression. First, every single objective is solved to get utilization by complex method, then, a novel concept of utilization vector is proposed to calculate the weighting coefficients to resolve the MOO problem, by chaotic local search particle swarm optimization with the constraints as penalty functions. MOO design methods are applied for one type of two-degree-of-freedom hybrid MB, and this method could obtain a better balanced overall result, improving the levitated force and decreasing flux density in the air gap.
引用
收藏
页数:14
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