Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms

• Main Authors: Hambali, Nurul Faqihah, Norsahperi, Nor Mohd Haziq, Mohd Hisban, Mas Athirah, Hassan, Mohd Khair, Wan Hasan, Wan Zuha, Ismail, Luthffi Idzhar, Ramli, Hafiz Rashidi
• Format: Conference or Workshop Item
• Published: Springer 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/108366/; https://link.springer.com/chapter/10.1007/978-981-99-8819-8_47

This study compares the performances of the GA-FOPID and MOGA-FOPID controllers, which are Fractional Order Proportional-Integral-Derivative (FOPID) controllers tuned using genetic algorithm and multiple-objective genetic algorithm for position tracking accuracy of robotic manipulator, respectively. The tuning process of six control gains in the three FOPID controllers is technically challenging to achieve high position accuracy of robotic manipulator. This study is performed to objectively assess the performances of genetic algorithm and multiple-objective genetic algorithm in tuning the six control gains in the FOPID controller. From the simulation study, it is interesting to note that the GA-FOPID and MOGA-FOPID controllers produce approximately 4.18 and 4.37 reductions of the mean square error in the angular position accuracy response of robotic manipulator as compared with the GA-PID controller. It is envisaged that the GA-FOPID and MOGA-FOPID controllers can be useful in designing effective position tracking accuracy of robotic manipulators.