Please use this identifier to cite or link to this item: https://doi.org/10.1109/TSMCB.2004.833340
Title: Robust adaptive neural network control of uncertain nonholonomic systems with strong nonlinear drifts
Authors: Wang, Z.P. 
Ge, S.S. 
Lee, T.H. 
Issue Date: Oct-2004
Citation: Wang, Z.P., Ge, S.S., Lee, T.H. (2004-10). Robust adaptive neural network control of uncertain nonholonomic systems with strong nonlinear drifts. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34 (5) : 2048-2059. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCB.2004.833340
Abstract: In this paper, robust adaptive neural network (NN) control is presented to solve the control problem of nonholonomic systems in chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive NN control laws are developed using state scaling and backstepping. Uniform ultimate boundedness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neighborhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. The proposed adaptive NN control is free of control singularity problem. An adaptive control based switching strategy is used to overcome the uncontrollability problem associated with χ0 (t0) = 0. The simulation results demonstrate the effectiveness of the proposed controllers. © 2004 IEEE.
Source Title: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
URI: http://scholarbank.nus.edu.sg/handle/10635/82986
ISSN: 10834419
DOI: 10.1109/TSMCB.2004.833340
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