Adaptive neural control of non-affine pure-feedback systems

Gong Wang; David J. Hill; Shuzhi S. Ge

doi:10.1109/.2005.1467031

Adaptive neural control of non-affine pure-feedback systems

Gong Wang^*, David J. Hill, Shuzhi S. Ge

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Controlling non-affine nonlinear systems is a challenging problem in the control community. In this paper, an adaptive neural control approach is presented for the completely non-affine pure-feedback system with only one mild assumption. By combining adaptive neural design with input-to-state stability (ISS) analysis and the small-gain theorem, the difficulty in controlling non-affine pure-feedback system is overcome by achieving the so-called "ISS-modularity" of the controller-estimator. The ISS-modular approach provides an effective way for controlling non-affine nonlinear systems with uncertainties. Simulation studies are included to demonstrate the effectiveness of the proposed approach.

Original language	English
Title of host publication	Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05
Pages	298-303
Number of pages	6
DOIs	https://doi.org/10.1109/.2005.1467031
Publication status	Published - 2005
Event	20th IEEE International Symposium on Intelligent Control, ISIC '05 and the13th Mediterranean Conference on Control and Automation, MED '05 - Limassol, Cyprus Duration: 27 Jun 2005 → 29 Jun 2005

Publication series

Name	Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05
Volume	2005

Conference

Conference	20th IEEE International Symposium on Intelligent Control, ISIC '05 and the13th Mediterranean Conference on Control and Automation, MED '05
Country/Territory	Cyprus
City	Limassol
Period	27/06/05 → 29/06/05

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Wang, G., Hill, D. J., & Ge, S. S. (2005). Adaptive neural control of non-affine pure-feedback systems. In Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05 (pp. 298-303). Article 1467031 (Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05; Vol. 2005). https://doi.org/10.1109/.2005.1467031

Wang, Gong ; Hill, David J. ; Ge, Shuzhi S. / Adaptive neural control of non-affine pure-feedback systems. Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05. 2005. pp. 298-303 (Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05).

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title = "Adaptive neural control of non-affine pure-feedback systems",

abstract = "Controlling non-affine nonlinear systems is a challenging problem in the control community. In this paper, an adaptive neural control approach is presented for the completely non-affine pure-feedback system with only one mild assumption. By combining adaptive neural design with input-to-state stability (ISS) analysis and the small-gain theorem, the difficulty in controlling non-affine pure-feedback system is overcome by achieving the so-called {"}ISS-modularity{"} of the controller-estimator. The ISS-modular approach provides an effective way for controlling non-affine nonlinear systems with uncertainties. Simulation studies are included to demonstrate the effectiveness of the proposed approach.",

author = "Gong Wang and Hill, {David J.} and Ge, {Shuzhi S.}",

year = "2005",

doi = "10.1109/.2005.1467031",

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series = "Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05",

pages = "298--303",

booktitle = "Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05",

note = "20th IEEE International Symposium on Intelligent Control, ISIC '05 and the13th Mediterranean Conference on Control and Automation, MED '05 ; Conference date: 27-06-2005 Through 29-06-2005",

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Wang, G, Hill, DJ & Ge, SS 2005, Adaptive neural control of non-affine pure-feedback systems. in Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05., 1467031, Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05, vol. 2005, pp. 298-303, 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the13th Mediterranean Conference on Control and Automation, MED '05, Limassol, Cyprus, 27/06/05. https://doi.org/10.1109/.2005.1467031

Adaptive neural control of non-affine pure-feedback systems. / Wang, Gong; Hill, David J.; Ge, Shuzhi S.
Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05. 2005. p. 298-303 1467031 (Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Controlling non-affine nonlinear systems is a challenging problem in the control community. In this paper, an adaptive neural control approach is presented for the completely non-affine pure-feedback system with only one mild assumption. By combining adaptive neural design with input-to-state stability (ISS) analysis and the small-gain theorem, the difficulty in controlling non-affine pure-feedback system is overcome by achieving the so-called "ISS-modularity" of the controller-estimator. The ISS-modular approach provides an effective way for controlling non-affine nonlinear systems with uncertainties. Simulation studies are included to demonstrate the effectiveness of the proposed approach.

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Wang G, Hill DJ, Ge SS. Adaptive neural control of non-affine pure-feedback systems. In Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05. 2005. p. 298-303. 1467031. (Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05). doi: 10.1109/.2005.1467031

Adaptive neural control of non-affine pure-feedback systems

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