Modeling of flexible manipulator structure using particle swarm optimization with Explorer

Abstract

This paper presents an investigation into the development of novel Particle Swarm Optimization with Explorer and its application to system identification for a single-link flexible manipulator system. A simulation environment characterizing the dynamic behavior of the flexible manipulator system was first developed using finite difference (FD) method to acquire the input-output data of the system. In this study, system identification scheme is developed to obtain a dynamic model of the manipulator in parametric form using Particle Swarm Optimization with Explorer. The introduction of explorer solves problem of getting stuck at local minima, thus proposed a novel methodology namely as Particle Swarm Optimization with Explorer (PSOE). Its performance is assessed in comparison to a standard Particle Swarm Optimization in characterizing the flexible manipulator structure. Results demonstrate the advantages of Particle Swarm Optimization with Explorer over their standard counterpart in system identification.