Abstract

This paper investigates the use of three control techniques to improve the trajectory tracking of a 3-DOF robotic arm. Specifically, Fuzzy Logic Control, Adaptive Neuro Fuzzy Inference System-based control, and a Genetic Algorithm (GA)-enhanced fuzzy controller are examined, with the objective of improving tracking accuracy and handling disturbances and parameter variations. Models were derived, and controllers’ performance was evaluated using MATLAB/Simulink. Results showed that the GA-optimized fuzzy controller outperformed the others, achieving the highest accuracy and stability. Under external disturbances, the GA-optimized fuzzy controller maintained strong performance, achieving an average root mean square error (RMSE) reduction of 89% compared to the feedback linearization controller (FBLC), and reductions of 95% and 91% compared to conventional fuzzy logic control (FLC) and Adaptive Neuro-Fuzzy Inference System (ANFIS). Moreover, under severe parameter variations, it demonstrated robust resilience, maintaining stable tracking with consistently low RMSE, whereas the FBLC failed. Findings suggest that the GA-optimized fuzzy controller provides an effective solution for applications where precision and resilience to external changes are critical.

About the Speaker

Mr. Asem Abdalhadi received his BEng degree in Mechatronics Engineering from the International Islamic University Malaysia (IIUM), Malaysia, and the MEng degree in Mechatronics Engineering from the University of Malaya (UM), Malaysia. He is currently pursuing a Ph.D. degree in Systems and Control Engineering in the Control and Instrumentation Engineering Department at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. His research interests include adaptive, robust, and intelligent control of robotic systems, observer design, and parameter estimation. His current research focuses on torque control and thermal derating in electric vehicle motor drives, emphasizing field-oriented control and estimation-based approaches.