Stability and robustness analysis of a class of adaptive controllers for robotic manipulators
International Journal of Robotics Research
Control Theory of Nonlinear Mechanical Systems
Control Theory of Nonlinear Mechanical Systems
Robot Dynamics and Control
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
Robust Tracking Control of Robot Manipulators
Robust Tracking Control of Robot Manipulators
Control of Robot Manipulators
IEEE Transactions on Robotics
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In this paper, two nonlinear control methods including adaptive learning control and adaptive robust control are designed for a robotic manipulator with time-varying uncertainties. We first present an adaptive learning control by incorporated learning control approaches into an adaptive control system to handle periodic uncertainties with known periods. We explore Lyapunov functional method to design the controller such that the convergence of tracking errors can be ensured. If the periods of uncertaines are unknown or uncertainties are non-periodic, an adaptive robust control is further designed to guarantee that the solution trajectory is finite and arbitrarily close to the desired trajectory by choosing design parameters in the controller. The efficacy of the proposed nonlinear controllers has been demonstrated in a two-link robot manipulator.