Hybrid control strategies for a five-finger robotic hand

This paper presents a hybrid controller of soft control techniques, adaptive neuro-fuzzy inference system (ANFIS) and fuzzy logic (FL), and hard control technique, proportional-derivative (PD), for a five-finger robotic hand with 14-degrees-of-freedom (DoF). The ANFIS is used for inverse kinematics of three-link fingers and FL is used for tuning the PD parameters with 2 input layers (error and error rate) using 7 triangular membership functions and 49 fuzzy logic rules. Simulation results with the hybrid of FL-tuned PD controller exhibit superior performance compared to PD, PID and FL controllers alone.

► A 14-Degree-of-Freedom, five-finger robotic hand with hybrid control strategies is presented. ► The hybrid technique involves soft computing with adaptive neuro-fuzzy inference system (ANFIS) and fuzzy logic (FL) and hard computing with proportional-derivative (PD) control. ► The ANFIS is used for inverse kinematics and FL is used for tuning the PD parameters. ► Simulation results with FL-tuned PD (hybrid) controller show superior performance compared to hard control (PD and PID controllers) and soft computing (FL controller) alone. ► The hybrid control strategies can be potentially applied for industrial and clinical applications.