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Lyapunov-based output feedback learning control of robot manipulators

This paper address the output feedback learning tracking control problem for robot manipulators with repetitive desired joint level trajectories. Specifically, an observer-based output feedback learning controller for periodic trajectories with known period have been proposed. The proposed learning controller guarantees semi-global asymptotic tracking despite the existence of parametric uncertainties associated with the robot dynamics and lack of velocity measurements. A learning-based feedforward term in conjunction with a novel observer formulation is designed to obtain the aforementioned result. The stability of the controller-observer couple is guaranteed via Lyapunov based arguments. Numerical studies performed on a two link robot manipulator are also presented to demonstrate the viability of the proposed method.