Firefly Algorithm for Modeling of Flexible Manipulator System

• Published in: Lecture Notes in Electrical Engineering
• Main Author: Baseri H.H.; Mohd Yatim H.; Hadi M.S.; Ab. Talib M.H.; Mat Darus I.Z.
• Format: Conference paper
• Language: English
• Published: Springer Science and Business Media Deutschland GmbH 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112546378&doi=10.1007%2f978-981-33-4597-3_23&partnerID=40&md5=a54e4706e5e00dca80d3b3ba9ebde886

Flexible manipulator is a general-purpose machine used for industrial automation in order to increase productivity, flexibility and product quality that has been widely applied to replace their rigid manipulator counterparts. Flexible manipulator is a distributed parameter system and has infinitely many degrees of freedom. However, flexible manipulator will develop unwanted vibration during manoeuvre that may reduce the efficiency of the flexible manipulator system for precise positioning requirements. Thus, the dynamics of this system are highly non-linear and complex. Therefore, an accurate model and efficient control system must be developed in order to sustain the advantages of the flexible manipulator system. This paper highlights the flexible manipulator modelling using system identification (SI) method employing Firefly Algorithm (FA). Initially, flexible manipulator test rig is developed for input output data collection. Behaviour of system response including hub angle and end-point acceleration are acquired and analyse. Later, data collected is fed into system identification method optimized by Firefly Algorithm via linear auto regressive with exogenous (ARX) model structure. Validations of the algorithm is assessed on basis of minimizing the mean-squared error (MSE) and correlation tests. It is demonstrated that FA modeling is superior that conventional algorithm known as Least Square (LS) Algorithm with lowest MSE obtained and achieved 95% confidence interval in correlation tests for both hub angle and end-point acceleration identification. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.