Simultaneous Model Order and Parameter Estimation (SMOPE) based on Random Asynchronous Particle Swarm Optimization

Abstract


 
 
 
 Simultaneous model order and parameter estimation (SMOPE) is a metaheuristic based system identification method. SMOPE was introduced using particle swarm optimization (PSO). There are several iteration strategies for PSO. The original work on SMOPE is based on synchronous PSO (S-PSO). However, in some works PSO using other iteration strategy is found to give better results. In this work, based on six system identification problems random asynchronous (RA-PSO) based SMOPE is found to have slight advantage over S-PSO.