Adaptive dynamic surface control of a flexible-joint robot with parametric uncertainties
A new kind of adaptive dynamic surface control (DSC) method is proposed to overcome parametric uncertainties of flexible-joint (FJ) robots. These uncertainties of FJ robots are transformed into linear expressions of inertial parameters which are estimated based on the DSC, and the high-order derivatives in DSC are solved by using first-order filter. The adaptation laws of inertial parameters are designed directly to improve the tracking performance according to the Lyapunov stability analysis. Simulation results for a two-link FJ robot show the better tracking accuracy against model parametric uncertainties. The method used does not need aid of Neural Network (NN), and is simpler and calculation faster than the other adaptive methods
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