Active electromagnetic suspension system design using hybrid neural-swarm optimization

Abstract

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.

Characteristics and Analysis of an Eddy Current Shock Absorber Damper Using Finite Element Analysis

“…Examples include the investigation of a dynamic model for an eddy current damper (ECD) in [8] and the formulation of an improved and more accurate theoretical model of ECD system in [9]. Moreover, novel ECD configurations have been also introduced recently [10][11][12][13][14][15][16]. Those studies clearly highlight the main advantages of ECDs.…”