Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2010.5524379
Title: Robust adaptive neuro-fuzzy control of uncertain nonholonomic systems
Authors: Hong, F.
Ge, S.S. 
Pang, C.K. 
Lee, T.H. 
Sun, Z.
Keywords: Motion control
Neuro-fuzzy control
Nonholonomic systems
Issue Date: 2010
Citation: Hong, F.,Ge, S.S.,Pang, C.K.,Lee, T.H.,Sun, Z. (2010). Robust adaptive neuro-fuzzy control of uncertain nonholonomic systems. 2010 8th IEEE International Conference on Control and Automation, ICCA 2010 : 2201-2206. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCA.2010.5524379
Abstract: In this paper, we present an adaptive neuro-fuzzy controller design for a class of uncertain nonholonomic systems in the perturbed chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive neuro-fuzzy control laws are developed using state scaling and backstepping. Semi-global 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. By using fuzzy logic approximation, the proposed control is free of control singularity problem. An adaptive control based switching strategy is proposed to overcome the uncontrollability problem associated with x0(t0) = 0. © 2010 IEEE.
Source Title: 2010 8th IEEE International Conference on Control and Automation, ICCA 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/84142
ISBN: 9781424451951
DOI: 10.1109/ICCA.2010.5524379
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