Modeling of Flexible Manipulator Structure Using Genetic Algorithm with Parameter Exchanger

Abstract

This paper presents a novel Genetic Algorithms with Parameter Exchanger 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 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 Genetic Algorithms. A novel methodology of Genetic Algorithms namely as Genetic Algorithms with Parameter Exchanger (GAPE) was proposed and its performance is assessed in comparison to a standard Genetic Algorithms in characterizing the flexible manipulator structure. Results demonstrate the advantages of Genetic Algorithm with Parameter Exchanger over their standard counterpart in parametric identification.