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Direct adaptive NN control of a class of nonlinear systems

Ge, S.S., Cong Wang·2002·IEEE Transactions on Neural Networks

Abstract

In this paper, direct adaptive neural-network (NN) control is presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By utilizing a special property of the affine term, the developed scheme,avoids the controller singularity problem completely. All the signals in the closed loop are guaranteed to be semiglobally uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation results are presented to show the effectiveness of the approach.

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Metadata

Authors
Ge, S. S., & Wang, C.
Venue
IEEE Transactions on Neural Networks
Published
2002
Volume
13
Issue
1
Pages
214-221
ISSN
1045-9227 (ISSN-L)
OpenAlex
W2133869087
Cited by
618
References
0
FWCI
22.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Direct adaptive NN control of a class of nonlinear systems. https://app.cochat.ai/papers/10.1109/72.977306
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Ge, S. S., & Wang, C. (2002). Direct adaptive NN control of a class of nonlinear systems. IEEE Transactions on Neural Networks. https://doi.org/10.1109/72.977306

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.