Adaptive Visual Tracking Control for Manipulator With Actuator Fuzzy Dead-Zone Constraint and Unmodeled Dynamic

This paper focuses on a problem of adaptive visual tracking control for an uncalibrated image-based visual servoing manipulator system with actuator fuzzy dead-zone constrain and unknown dynamic. Without a prior knowledge of the system, fuzzy logic systems are employed to approximate the unmodeled nonlinear manipulator dynamics and external disturbances. By using the recursive Newton–Euler method, the total number of fuzzy rules can be reduced significantly as compared with the traditional fuzzy logic system. By defuzzifying the fuzzy slope of the fuzzy dead-zone model to a deterministic value , a novel fuzzy adaptive controller is constructed to eliminate the harmful effect of fuzzy dead-zone constrain. Lyapunov functions are presented for stability analysis of visual feedback control problem with unknown dynamics and actuator fuzzy dead-zone constrains. Experimental results are carried out to test the visual tracking performance of the proposed controller and the boundedness of the closed-loop system.