Optimal Minimum Violation Control Synthesis of Cyber-Physical Systems Under Attacks

Temporal logic provides a rigorous and expressive way to model specifications for cyber-physical systems (CPS). Such systems, which are playing increasingly important roles in various domains, are also subject to malicious attacks initiated by intelligent adversaries. Malicious attacks may prevent t...

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Bibliographic Details
Published in:IEEE transactions on automatic control Vol. 66; no. 3; pp. 995 - 1008
Main Authors: Niu, Luyao, Fu, Jie, Clark, Andrew
Format: Journal Article
Language:English
Published: New York IEEE 01.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Approximation algorithms
Automata
Computational modeling
Controllers
Convergence
Cyber-physical systems
Games
Mixed integer
Optimal control
probabilistic logic
safety
Security
Specifications
Stochastic processes
Strategy
Synthesis
Temporal logic
ISSN:0018-9286, 1558-2523
Online Access:Get full text
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Summary:Temporal logic provides a rigorous and expressive way to model specifications for cyber-physical systems (CPS). Such systems, which are playing increasingly important roles in various domains, are also subject to malicious attacks initiated by intelligent adversaries. Malicious attacks may prevent the system from satisfying the desired specification. In this article, we introduce a control synthesis method to minimize deviations from the desired specification due to adversaries. We consider the scenario where the adversary has limited capability of observing the controller's strategy. We synthesize a minimum violation control strategy for a finite-state stochastic game under cosafe linear temporal logic constraints. We formulate a mixed-integer nonlinear program for computing the optimal controller strategy and present two algorithms. First, we propose an exact algorithm that computes the optimal control strategy with probability one but without guarantees on the convergence rate. Second, we present an approximate algorithm that computes a suboptimal control strategy. The approximate algorithm converges faster compared to the exact algorithm; however, it only returns an optimal solution when the adversary has full observation over the controller's strategy. A numerical case study is presented to evaluate the proposed framework.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2020.2989268