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Brief Papers Adaptive Control for Nonlinearly Parameterized Uncertainties in Robot Manipulators

By N. V. Q. Hung, H. D. Tuan, T. Narikiyo and P. Apkarian


Abstract—In this brief, a new adaptive control framework to compensate for uncertain nonlinear parameters in robot manipulators is developed. The designed adaptive controllers possess a linear parameter structure, guarantee global boundedness of the closed-loop system as well as tracking of a given trajectory within any prescribed accuracy. Our design approach takes advantage of a Lipschitzian property with respect to the plant nonlinear parameters. The outcome is that a very broad class of nonlinearly parameterized adaptive control problems for robot manipulators can be solved using this technique. Another feature of the proposed method is the design of low-dimensional estimator, even 1-D if desired, independently of the unknown parameter vector dimension. Simulations and experiments in friction compensation task for low-velocity tracking of a 2 degree-of-freedom planar robot demonstrate the viability of the technique and emphasize its advantages relatively to more classical approaches. Index Terms—Adaptive control, friction compensation, motion control, nonlinearities, parameter estimation, robot control, uncertain systems. I

Year: 2011
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