摘要

Recently, utilization of electromagnetic suspension systems has been on the rise as a result of novel space and automotive-related industrial applications. This paper presents an efficient iterative hybrid neural-swarm optimization methodology for electromagnetic suspension system design involving nonlinear magnetic media. Within this approach, 2D field computations are carried out using the integral equation approach in an automated mechanism through continuous Hopfield neural network (HNN) implementation. Optimal dimensions of the system are identified through the minimization of an error function of some target performance using the particle swarm optimization (PSO) evolutionary approach. Details of the approach and sample design examples are given in the paper.

  • 出版日期2013