Discrete-Time Adaptive Controller Design for Robotic Manipulators via Neuro-fuzzy Dynamic Inversion

A stable discrete-time adaptive tracking controller using neuro–fuzzy (NF) dynamic inversion is proposed for a robotic manipulator with its dynamics approximated by a dynamic T-S fuzzy model. NF dynamic inversion is used to compensate for the robot inverse dynamics. By assigning the dynamics of the Dynamic NF (DNF) system, the dynamic performance of the robot control system can be guaranteed in the initial control stage. The discrete-time adaptive control composed of NF dynamic inversion and NF variable structure control (NF-VSC) is developed to stabilize the closed-loop system and ensure the high-quality tracking. The system stability and the convergence of tracking errors are guaranteed and effectiveness of the proposed control approach. is verified.