Cuckoo Search for Modelling of a Flexible Single-Link Manipulator

摘要

This study presents the development of approaches with Cuckoo Search algorithm and Particle Swarm Optimization technique for modelling of a flexible single-link manipulator. Finite element method and Lagrangian approaches were used to acquire the input-output data of the system. A bang-bang input torque was applied and the dynamic response of the system was investigated. Next, a suitable model structure was selected and optimized using an intelligent parametric identification technique of Cuckoo Search algorithm and Particle Swarm Optimization techniques. Mean squared error, One Step Ahead prediction, correlation tests have been performed for validation and verification of the obtained model in characterizing the manipulator system. A comparative assessment of the two models in characterizing the manipulator system is presented in time and frequency domains. Results demonstrate the advantages of Cuckoo Search algorithm over Particle Swarm Optimization in parametric modeling of the flexible single-link manipulator.