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Cited by 297

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Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time

Long, Lijun, Zhao, Jun·2015·IEEE Transactions on Neural Networks and Learning Systems

Abstract

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

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Metadata

Authors
Long, L., & Zhao, J.
Venue
IEEE Transactions on Neural Networks and Learning Systems
Published
2015-07
Volume
26
Issue
7
Pages
1350-1362
ISSN
  • 2162-237X (ISSN-L)
  • 2162-2388
OpenAlex
W2171052973
Cited by
297
References
1
FWCI
26.05
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time. https://app.cochat.ai/papers/10.1109/tnnls.2014.2341242
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Long, L., & Zhao, J. (2015). Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2014.2341242

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