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 k̅ of the fuzzy dead-zone model to a deterministic value k̅, 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.

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