Secure Multiplicative Sampled-Data Control for T-S Fuzzy-Based Cyber-Physical Systems Subject to Deception Attacks
This work addresses the secure control problem of T-S fuzzy-based cyber-physical systems (TSFCPSs) under randomly occurring deception attacks (RODAs). Random variables following the Bernoulli distribution are used to model the probability of false data injection by malicious adversaries. A novel mem...
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Published in | Circuits, systems, and signal processing Vol. 44; no. 3; pp. 1697 - 1725 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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01.03.2025
Springer Nature B.V |
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Abstract | This work addresses the secure control problem of T-S fuzzy-based cyber-physical systems (TSFCPSs) under randomly occurring deception attacks (RODAs). Random variables following the Bernoulli distribution are used to model the probability of false data injection by malicious adversaries. A novel memory-based sampled-data control (MSDC) scheme is developed to counter RODAs and multiplicative control gain uncertainties (MCGUs), both of which follow the Bernoulli distribution. The MSDC design for the TSFCPSs considers information over the entire sampling interval,
t
k
to
t
k
+
1
, and accounts for signal transmission delays in relation to the augmented state vectors. The looped functional (LF) approach is employed to address the formulated Lyapunov-Krasovskii functional. New stabilization criteria, based on the LF method, are derived in terms of linear matrix inequalities to ensure the proposed TSFCPSs are asymptotically stable despite RODAs and MCGUs. An illustrative example of a power system with a doubly-fed induction generator-based wind turbine demonstrates the effectiveness and advantages of the proposed MSDC in achieving the desired performance. |
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AbstractList | This work addresses the secure control problem of T-S fuzzy-based cyber-physical systems (TSFCPSs) under randomly occurring deception attacks (RODAs). Random variables following the Bernoulli distribution are used to model the probability of false data injection by malicious adversaries. A novel memory-based sampled-data control (MSDC) scheme is developed to counter RODAs and multiplicative control gain uncertainties (MCGUs), both of which follow the Bernoulli distribution. The MSDC design for the TSFCPSs considers information over the entire sampling interval, tk to tk+1, and accounts for signal transmission delays in relation to the augmented state vectors. The looped functional (LF) approach is employed to address the formulated Lyapunov-Krasovskii functional. New stabilization criteria, based on the LF method, are derived in terms of linear matrix inequalities to ensure the proposed TSFCPSs are asymptotically stable despite RODAs and MCGUs. An illustrative example of a power system with a doubly-fed induction generator-based wind turbine demonstrates the effectiveness and advantages of the proposed MSDC in achieving the desired performance. This work addresses the secure control problem of T-S fuzzy-based cyber-physical systems (TSFCPSs) under randomly occurring deception attacks (RODAs). Random variables following the Bernoulli distribution are used to model the probability of false data injection by malicious adversaries. A novel memory-based sampled-data control (MSDC) scheme is developed to counter RODAs and multiplicative control gain uncertainties (MCGUs), both of which follow the Bernoulli distribution. The MSDC design for the TSFCPSs considers information over the entire sampling interval, t k to t k + 1 , and accounts for signal transmission delays in relation to the augmented state vectors. The looped functional (LF) approach is employed to address the formulated Lyapunov-Krasovskii functional. New stabilization criteria, based on the LF method, are derived in terms of linear matrix inequalities to ensure the proposed TSFCPSs are asymptotically stable despite RODAs and MCGUs. An illustrative example of a power system with a doubly-fed induction generator-based wind turbine demonstrates the effectiveness and advantages of the proposed MSDC in achieving the desired performance. |
Author | Lakshmanan, S. Arunagirinathan, S. Lee, T. H. |
Author_xml | – sequence: 1 givenname: S. surname: Arunagirinathan fullname: Arunagirinathan, S. organization: Division of Electronic Engineering, Jeonbuk National University – sequence: 2 givenname: S. surname: Lakshmanan fullname: Lakshmanan, S. organization: Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology-Chennai – sequence: 3 givenname: T. H. orcidid: 0000-0003-3953-6913 surname: Lee fullname: Lee, T. H. email: fesuselee@gmail.com organization: Division of Electronic Engineering, Jeonbuk National University |
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Keywords | Sampled-data control Lyapunov method Power System control problem Deception-attacks T-S fuzzy system |
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SubjectTerms | Circuits and Systems Control systems Cyber-physical systems Electrical Engineering Electronics and Microelectronics Engineering Induction generators Information systems Instrumentation Linear matrix inequalities Random variables Signal transmission Signal,Image and Speech Processing State vectors Wind turbines |
Title | Secure Multiplicative Sampled-Data Control for T-S Fuzzy-Based Cyber-Physical Systems Subject to Deception Attacks |
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