Exponential inertia weight particle swarm algorithm for dynamics optimization of electromechanical coupling system

Abstract

Aiming at the electromechanical coupling system dynamics optimization of spindle unit of refitted machine tool for solid rocket, the optimization modeling is presented on the basis of system differential equations. The research job in the paper reveals that the global optimization efficiency can be enhanced greatly, when the weight value of the swarm particle algorithm can be changed with special exponential function. So, a kind of new particle swarm algorithm, Exponential inertia weight Particle Swarm Optimization (EPSO), is formed by adopting exponential inertia weight function. Based on above research job, the optimized design parameters of the spindle unit of refitted machine tool for solid rocket are obtained in limit time period, and the engineering problem of dynamic optimization of electromechanical system is solved successfully by the method of EPSO. The results are the innovative achievements in the field of mechatronics, and have broad application prospects in the design of robots, NC machine, and electromechanical equipments.