Robust Adaptive Fuzzy Output Feedback Control System for Robot Manipulators

In this paper, we propose a novel hybrid control system for the trajectory tracking control problem of robotic systems. The design combines fuzzy system with robust adaptive control algorithm. The fuzzy system approximates the certainty equivalent-based optimal controller, while a robustifying adaptive control term is used to cope with uncertainties due to the presence of the external disturbance, fuzzy approximation errors, and other modeling errors. Using the Lyapunov method, we first develop a stable hybrid controller by assuming that the system output and its derivatives are available for feedback control design. Then, an output-feedback form of the position-velocity (state-feedback) controller is proposed, where the unknown velocity signal is replaced by the output of a model-free linear estimator. We show that the tracking of the output-feedback design can converge asymptotically to the performance achieved under the state-feedback control design. Finally, the proposed method is evaluated on a robotic system to demonstrate the theoretical development.