Multi-objective optimization design of single-stage electromagnetic needle selector with permanent magnet

Abstract

A multi-objective optimization method for electromagnetic actuator with permanent magnet is presented in this paper. The OLS-RBF neural network is improved by introducing gradient descent operator, and the coupling relationship between optimization objective and optimization factor of electromagnetic actuator with permanent magnet is fitted. NSGA-II algorithm is used to solve the multi-objective optimization of the approximate model obtained by fitting, and its effectiveness and feasibility are verified by simulation.