Fixed-endpoint minimum-energy control of bilinear ensemble systems

Shuo Wang; Jr Shin Li

doi:10.1109/CDC.2015.7402355

Fixed-endpoint minimum-energy control of bilinear ensemble systems

Shuo Wang, Jr Shin Li

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

8 Scopus citations

Abstract

Optimal control of bilinear systems has been a well-studied subject in the area of mathematical control. However, effective methods for solving the emerging optimal control problems involving an ensemble of bilinear systems are underdeveloped. In this work, we present an iterative method to effectively solve these challenging optimal control problems, in which at each iteration the bilinear ensemble system is represented as a time-varying linear ensemble system and then the optimal ensemble control is obtained by using an SVD-based computational algorithm designed for solving optimal control problems for linear ensemble systems. We analyze the convergence of the developed iterative method and provide examples of practical ensemble control designs in magnetic resonance to demonstrate its applicability.

Original language	English
Title of host publication	54rd IEEE Conference on Decision and Control,CDC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1078-1083
Number of pages	6
ISBN (Electronic)	9781479978861
DOIs	https://doi.org/10.1109/CDC.2015.7402355
State	Published - Feb 8 2015
Event	54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan Duration: Dec 15 2015 → Dec 18 2015

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	54th IEEE Conference on Decision and Control, CDC 2015
Country/Territory	Japan
City	Osaka
Period	12/15/15 → 12/18/15

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10.1109/CDC.2015.7402355

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Wang, S., & Li, J. S. (2015). Fixed-endpoint minimum-energy control of bilinear ensemble systems. In 54rd IEEE Conference on Decision and Control,CDC 2015 (pp. 1078-1083). Article 7402355 (Proceedings of the IEEE Conference on Decision and Control; Vol. 54rd IEEE Conference on Decision and Control,CDC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2015.7402355

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title = "Fixed-endpoint minimum-energy control of bilinear ensemble systems",

abstract = "Optimal control of bilinear systems has been a well-studied subject in the area of mathematical control. However, effective methods for solving the emerging optimal control problems involving an ensemble of bilinear systems are underdeveloped. In this work, we present an iterative method to effectively solve these challenging optimal control problems, in which at each iteration the bilinear ensemble system is represented as a time-varying linear ensemble system and then the optimal ensemble control is obtained by using an SVD-based computational algorithm designed for solving optimal control problems for linear ensemble systems. We analyze the convergence of the developed iterative method and provide examples of practical ensemble control designs in magnetic resonance to demonstrate its applicability.",

author = "Shuo Wang and Li, {Jr Shin}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 54th IEEE Conference on Decision and Control, CDC 2015 ; Conference date: 15-12-2015 Through 18-12-2015",

year = "2015",

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doi = "10.1109/CDC.2015.7402355",

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Wang, S & Li, JS 2015, Fixed-endpoint minimum-energy control of bilinear ensemble systems. in 54rd IEEE Conference on Decision and Control,CDC 2015., 7402355, Proceedings of the IEEE Conference on Decision and Control, vol. 54rd IEEE Conference on Decision and Control,CDC 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1078-1083, 54th IEEE Conference on Decision and Control, CDC 2015, Osaka, Japan, 12/15/15. https://doi.org/10.1109/CDC.2015.7402355

Fixed-endpoint minimum-energy control of bilinear ensemble systems. / Wang, Shuo; Li, Jr Shin.
54rd IEEE Conference on Decision and Control,CDC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1078-1083 7402355 (Proceedings of the IEEE Conference on Decision and Control; Vol. 54rd IEEE Conference on Decision and Control,CDC 2015).

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

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N2 - Optimal control of bilinear systems has been a well-studied subject in the area of mathematical control. However, effective methods for solving the emerging optimal control problems involving an ensemble of bilinear systems are underdeveloped. In this work, we present an iterative method to effectively solve these challenging optimal control problems, in which at each iteration the bilinear ensemble system is represented as a time-varying linear ensemble system and then the optimal ensemble control is obtained by using an SVD-based computational algorithm designed for solving optimal control problems for linear ensemble systems. We analyze the convergence of the developed iterative method and provide examples of practical ensemble control designs in magnetic resonance to demonstrate its applicability.

AB - Optimal control of bilinear systems has been a well-studied subject in the area of mathematical control. However, effective methods for solving the emerging optimal control problems involving an ensemble of bilinear systems are underdeveloped. In this work, we present an iterative method to effectively solve these challenging optimal control problems, in which at each iteration the bilinear ensemble system is represented as a time-varying linear ensemble system and then the optimal ensemble control is obtained by using an SVD-based computational algorithm designed for solving optimal control problems for linear ensemble systems. We analyze the convergence of the developed iterative method and provide examples of practical ensemble control designs in magnetic resonance to demonstrate its applicability.

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Fixed-endpoint minimum-energy control of bilinear ensemble systems

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