Adaptive Control of Robotic Dynamic Systems Based on Fuzzy Basis Function Networks

This paper presents a FBFN-based (Fuzzy Basis Function Network) adaptive control algorithm for uncertain robot manipulators. According to the nominal mode, the corresponding control law was designed. However, there always exists discrepancy between nominal and actual mode, and the FBFN was applied to approximate the uncertainty. After that, the adaptive law was designed to update the parameters of FBFN. Based on the theory of Lyapunov stability, the stability of the adaptive controller was given with a sufficient condition. A two-arm robot is simulated to verify the feasibility of the proposed control scheme.