Lyapunov stability criterion based neural inverse tracking for unknown dynamic plants

Muhammad Saleheen Aftab; Muhammad Shafiq; Hasan Yousef

doi:10.1109/ICIT.2015.7125118

Lyapunov stability criterion based neural inverse tracking for unknown dynamic plants

Muhammad Saleheen Aftab, Muhammad Shafiq, Hasan Yousef

Electrical and Computer Engineering

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

4 Citations (Scopus)

Abstract

This paper presents a Lyapunov function based neural network tracking control strategy for single-input-single-output nonlinear dynamic systems. The proposed architecture is composed of two feed-forward neural networks operating as controller and estimator in a unified framework. The network parameters are tuned online with a Lyapunov function based backpropagation learning algorithm. The closed-loop error convergence and stability are analyzed with Lyapunov stability theory. Two simulation case studies are included that successfully validate the proposed controller performance.

Original language	English
Title of host publication	Proceedings of the IEEE International Conference on Industrial Technology
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	321-325
Number of pages	5
Volume	2015-June
Edition	June
DOIs	https://doi.org/10.1109/ICIT.2015.7125118
Publication status	Published - Jun 16 2015
Event	2015 IEEE International Conference on Industrial Technology, ICIT 2015 - Seville, Spain Duration: Mar 17 2015 → Mar 19 2015

Other

Other	2015 IEEE International Conference on Industrial Technology, ICIT 2015
Country	Spain
City	Seville
Period	3/17/15 → 3/19/15

Keywords

direct adaptive inverse control
indirect adaptive inverse control
Lyapunov function
neural inverse tracking
stable adaptive tracking

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Science Applications

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Lyapunov stability criterion based neural inverse tracking for unknown dynamic plants. / Aftab, Muhammad Saleheen; Shafiq, Muhammad ; Yousef, Hasan.

Proceedings of the IEEE International Conference on Industrial Technology. Vol. 2015-June June. ed. Institute of Electrical and Electronics Engineers Inc., 2015. p. 321-325 7125118.

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

Aftab, MS, Shafiq, M & Yousef, H 2015, Lyapunov stability criterion based neural inverse tracking for unknown dynamic plants. in Proceedings of the IEEE International Conference on Industrial Technology. June edn, vol. 2015-June, 7125118, Institute of Electrical and Electronics Engineers Inc., pp. 321-325, 2015 IEEE International Conference on Industrial Technology, ICIT 2015, Seville, Spain, 3/17/15. https://doi.org/10.1109/ICIT.2015.7125118

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AB - This paper presents a Lyapunov function based neural network tracking control strategy for single-input-single-output nonlinear dynamic systems. The proposed architecture is composed of two feed-forward neural networks operating as controller and estimator in a unified framework. The network parameters are tuned online with a Lyapunov function based backpropagation learning algorithm. The closed-loop error convergence and stability are analyzed with Lyapunov stability theory. Two simulation case studies are included that successfully validate the proposed controller performance.

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BT - Proceedings of the IEEE International Conference on Industrial Technology

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Lyapunov stability criterion based neural inverse tracking for unknown dynamic plants

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Keywords

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