Efficient control recovery for resilient control systems. / Zhang, Shuo; Wolthusen, Stephen.

2018. 1-6 Paper presented at 15th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China.

Research output: Contribution to conferencePaperpeer-review

Published

Standard

Efficient control recovery for resilient control systems. / Zhang, Shuo; Wolthusen, Stephen.

2018. 1-6 Paper presented at 15th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China.

Research output: Contribution to conferencePaperpeer-review

Harvard

Zhang, S & Wolthusen, S 2018, 'Efficient control recovery for resilient control systems', Paper presented at 15th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China, 27/03/18 - 29/03/18 pp. 1-6. https://doi.org/10.1109/ICNSC.2018.8361318

APA

Zhang, S., & Wolthusen, S. (2018). Efficient control recovery for resilient control systems. 1-6. Paper presented at 15th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China. https://doi.org/10.1109/ICNSC.2018.8361318

Vancouver

Zhang S, Wolthusen S. Efficient control recovery for resilient control systems. 2018. Paper presented at 15th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China. https://doi.org/10.1109/ICNSC.2018.8361318

Author

Zhang, Shuo ; Wolthusen, Stephen. / Efficient control recovery for resilient control systems. Paper presented at 15th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China.6 p.

BibTeX

@conference{8e09b2d0ed2c428a810f05550e69e110,
title = "Efficient control recovery for resilient control systems",
abstract = "Resilient control systems should efficiently restore control into physical systems not only after the sabotage of themselves, but also after breaking physical systems. To enhance resilience of control systems, and given an originally minimal-input controlled linear-time invariant(LTI) physical system, we address the problem of efficient control recovery into it after removing a known system vertex by finding the minimum number of inputs. According to the minimum input theorem, with a digraph embedded into LTI model and involving a precomputed maximum matching, this problem is modeled into recovering controllability of it after removing a known network vertex. Then, we recover controllability of the residual network by efficiently finding a maximum matching rather than recomputation. As a result, except for precomputing a maximum matching and predetermining the removed vertex, the worst-case execution time of control recovery into the residual LTI physical system is linear.",
keywords = "Resilient Control , Control recovery, Maximum Cardinality Matching",
author = "Shuo Zhang and Stephen Wolthusen",
year = "2018",
month = may,
day = "21",
doi = "10.1109/ICNSC.2018.8361318",
language = "English",
pages = "1--6",
note = "15th IEEE International Conference on Networking, Sensing and Control ; Conference date: 27-03-2018 Through 29-03-2018",
url = "https://icnsc2018.jnu.edu.cn/",

}

RIS

TY - CONF

T1 - Efficient control recovery for resilient control systems

AU - Zhang, Shuo

AU - Wolthusen, Stephen

PY - 2018/5/21

Y1 - 2018/5/21

N2 - Resilient control systems should efficiently restore control into physical systems not only after the sabotage of themselves, but also after breaking physical systems. To enhance resilience of control systems, and given an originally minimal-input controlled linear-time invariant(LTI) physical system, we address the problem of efficient control recovery into it after removing a known system vertex by finding the minimum number of inputs. According to the minimum input theorem, with a digraph embedded into LTI model and involving a precomputed maximum matching, this problem is modeled into recovering controllability of it after removing a known network vertex. Then, we recover controllability of the residual network by efficiently finding a maximum matching rather than recomputation. As a result, except for precomputing a maximum matching and predetermining the removed vertex, the worst-case execution time of control recovery into the residual LTI physical system is linear.

AB - Resilient control systems should efficiently restore control into physical systems not only after the sabotage of themselves, but also after breaking physical systems. To enhance resilience of control systems, and given an originally minimal-input controlled linear-time invariant(LTI) physical system, we address the problem of efficient control recovery into it after removing a known system vertex by finding the minimum number of inputs. According to the minimum input theorem, with a digraph embedded into LTI model and involving a precomputed maximum matching, this problem is modeled into recovering controllability of it after removing a known network vertex. Then, we recover controllability of the residual network by efficiently finding a maximum matching rather than recomputation. As a result, except for precomputing a maximum matching and predetermining the removed vertex, the worst-case execution time of control recovery into the residual LTI physical system is linear.

KW - Resilient Control

KW - Control recovery

KW - Maximum Cardinality Matching

U2 - 10.1109/ICNSC.2018.8361318

DO - 10.1109/ICNSC.2018.8361318

M3 - Paper

SP - 1

EP - 6

T2 - 15th IEEE International Conference on Networking, Sensing and Control

Y2 - 27 March 2018 through 29 March 2018

ER -