Evolutionary algorithm for identification of a flexible single-link manipulator system

Abstract

This study presents an investigation into dynamic modelling of a flexible single-link manipulator system using differential evolutionary technique (DE) and particle swarm optimization technique (PSO). Details of simulation study, Model Selection, optimization and result analysis are given in this study. The input-output data of the system were first acquired through the simulation study using finite element method (FDM) based on Lagrangian approach. A bang-bang torque was applied as an input and the dynamic responses of the system were investigated. Next, an appropriate model structure was chosen and optimized using DE and PSO. One Step Ahead (OSA) prediction, correlation tests and mean squared error (MSE) have been performed for validation and verification of the obtained model in characterizing the manipulator system. Furthermore, an unseen data was used to observe the prediction ability of the model. A comparative assessment of the two models in characterizing the manipulator system is presented in time and frequency domains. Results demonstrate the advantages of DE over PSO in parametric modeling of the flexible manipulator system used in this study.