Design of a fuzzy-genetic controller for an articulated robot gripper

• Main Authors: Espanola, Jason L., Bandala, Argel A., Vicerra, Ryan Rhay P., Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2019
• Subjects: Robots—Control systems; Robot hands; Fuzzy logic; Electrical and Electronics; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1868; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2867/type/native/viewcontent
• Institution: De La Salle University

In this study, a fuzzy logic controller (FLC) was designed to manipulate an articulated robot gripper. An idea from a previous study was utilized to enhance the performance of the FLC using genetic algorithms by optimizing newly-introduced coefficients in the membership functions of the FLC. The proposed controller was applied on a robot gripper model in Simulink. All in all, the genetic algorithm was able to come up with optimized parameters after an average of at least eight (8) generations and the proposed controller was able to follow the reference trajectory more accurately than the simple fuzzy controller. Further research will be necessary for physical implementation and possible improvement of the utilized genetic algorithm. © 2018 IEEE.