Visible to the public Efficient Control Recovery for Resilient Control Systems

TitleEfficient Control Recovery for Resilient Control Systems
Publication TypeConference Paper
Year of Publication2018
AuthorsZhang, S., Wolthusen, S. D.
Conference Name2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC)
ISBN Number978-1-5386-5053-0
KeywordsBipartite graph, computational complexity, control engineering computing, control recovery, control theory, Controllability, controllability recovering, Cyber-physical systems, digraph, directed graphs, known network vertex, known system vertex, Linear systems, LTI model, Mathematical model, maximum matching precomputing, minimal-input controlled linear-time invariant physical system, minimum input theorem, network theory (graphs), pubcrawl, recomputation, residual LTI physical system, residual network controllability, resilience, Resiliency, resilient control systems, System recovery, Time complexity, worst-case execution time
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, 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, given 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 the following removed vertex, the worst-case execution time of control recovery into the residual LTI physical system is linear.

URLhttps://ieeexplore.ieee.org/document/8361318
DOI10.1109/ICNSC.2018.8361318
Citation Keyzhang_efficient_2018