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Adaptive dynamic surface control of flexible-joint robot with parametric uncertainties

Chenggang Li, Wen Cui, Dengdeng Yan, Yan Wang, Chunming Wang

发表年份
2018
引用次数
4
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摘要

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

关键词

Control theory (sociology)Parametric statisticsRobotInertial frame of referenceArtificial neural networkComputer scienceAdaptive controlJoint (building)Stability (learning theory)Lyapunov function

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