Suction control of a robotic gripper: A neuro-fuzzy approach
This paper discusses a fuzzy logic control system designed to determine, regulate and maintain the amount of suction needed by a robotic gripper system to perform reliable limp material manipulation. A neuro-fuzzy approach is followed to determine the amount of desired suction (depending on experimentally derived data and plant characteristics). A knowledge-based valve controller is then designed to generate, regulate and maintain the amount of suction calculated by the neuro-fuzzy suction module. The performance of the overall suction control system is compared with actual experimental results obtained when using a prototype gripper system to handle limp material. Further, performance of the fuzzy logic based valve controller is compared to conventional PD and PID controllers. The proposed control scheme is found to enhance the overall functionality of the prototype robotic gripper system.
suction control robotic gripper limp material knowledge-based systems neuro-fuzzy control