期刊
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
卷 30, 期 6, 页码 753-766出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/3468.895898
关键词
adaptive; backstepping control; neural networks; nonlinear systems; robust
A controller is proposed for the robust backstepping control of a class of general nonlinear systems using neural networks (NNs), A new tuning scheme is proposed which can guarantee the boundedness of tracking error and weight updates, Compared with adaptive backstepping control schemes, we do not require the unknown parameters to be linear parametrizable, No regression matrices are needed, so no preliminary dynamical analysis is needed, One salient feature of our NN approach is that there is no need for the off-line learning phase. Three nonlinear systems, including a one-link robot, an induction motor, and a rigid-link flexible-joint robot, were used to demonstrate the effectiveness of the proposed scheme.
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