Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation

Xinyi Le; Jun Wang; Zheng Yan

doi:10.1109/INISTA.2014.6873589

Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation

Xinyi Le, Jun Wang, Zheng Yan

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

A neurodynamic optimization approach is proposed for robust pole assignment problem of second-order control systems via output feedback. With a suitable robustness measure serving as the objective function, the robust pole assignment problem is formulated as a quasi-convex optimization problem with linear constraints. Next, the problem further is reformulated as a convex feasibility problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach. © 2014 IEEE.

Original language	English
Title of host publication	INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings
Publisher	IEEE Computer Society
Pages	1-6
ISBN (Print)	9781479930197
DOIs	https://doi.org/10.1109/INISTA.2014.6873589
Publication status	Published - 2014
Externally published	Yes
Event	2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014 - Alberobello, Italy Duration: 23 Jun 2014 → 25 Jun 2014

Conference

Conference	2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014
Place	Italy
City	Alberobello
Period	23/06/14 → 25/06/14

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Le, X., Wang, J., & Yan, Z. (2014). Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation. In INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings (pp. 1-6). Article 6873589 IEEE Computer Society. https://doi.org/10.1109/INISTA.2014.6873589

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title = "Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation",

abstract = "A neurodynamic optimization approach is proposed for robust pole assignment problem of second-order control systems via output feedback. With a suitable robustness measure serving as the objective function, the robust pole assignment problem is formulated as a quasi-convex optimization problem with linear constraints. Next, the problem further is reformulated as a convex feasibility problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach. {\textcopyright} 2014 IEEE.",

author = "Xinyi Le and Jun Wang and Zheng Yan",

year = "2014",

doi = "10.1109/INISTA.2014.6873589",

language = "English",

isbn = "9781479930197",

pages = "1--6",

booktitle = "INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings",

publisher = "IEEE Computer Society",

address = "United States",

note = "2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014 ; Conference date: 23-06-2014 Through 25-06-2014",

}

Le, X, Wang, J & Yan, Z 2014, Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation. in INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings., 6873589, IEEE Computer Society, pp. 1-6, 2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014, Alberobello, Italy, 23/06/14. https://doi.org/10.1109/INISTA.2014.6873589

Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation. / Le, Xinyi; Wang, Jun; Yan, Zheng.
INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings. IEEE Computer Society, 2014. p. 1-6 6873589.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation

AU - Le, Xinyi

AU - Wang, Jun

AU - Yan, Zheng

PY - 2014

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N2 - A neurodynamic optimization approach is proposed for robust pole assignment problem of second-order control systems via output feedback. With a suitable robustness measure serving as the objective function, the robust pole assignment problem is formulated as a quasi-convex optimization problem with linear constraints. Next, the problem further is reformulated as a convex feasibility problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach. © 2014 IEEE.

AB - A neurodynamic optimization approach is proposed for robust pole assignment problem of second-order control systems via output feedback. With a suitable robustness measure serving as the objective function, the robust pole assignment problem is formulated as a quasi-convex optimization problem with linear constraints. Next, the problem further is reformulated as a convex feasibility problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach. © 2014 IEEE.

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U2 - 10.1109/INISTA.2014.6873589

DO - 10.1109/INISTA.2014.6873589

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781479930197

SP - 1

EP - 6

BT - INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings

PB - IEEE Computer Society

T2 - 2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014

Y2 - 23 June 2014 through 25 June 2014

ER -

Le X, Wang J, Yan Z. Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation. In INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings. IEEE Computer Society. 2014. p. 1-6. 6873589 doi: 10.1109/INISTA.2014.6873589

Neurodynamics-based robust pole assignment for synthesizing second-order control systems via output feedback based on a convex feasibility problem reformulation

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