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Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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Security control for networked control systems with deception attacks: A stochastic model predictive control

Zhaoke Ning1, Xinglian Zhou2, Juncong Yang3

  • 1Key Laboratory of Advanced Spatial Mechanism and Intelligent Spacecraft, Ministry of Education, School of Aeronautics and Astronautics, Sichuan University, Chengdu 610207, China.

ISA Transactions
|December 30, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a robust security control method for networked control systems facing stochastic deception attacks. The approach uses distributionally robust optimization and chance constraints to enhance system security and performance.

Keywords:
Chance constraintsDeception attacksDistributionally robust optimizationSecurity controlStochastic model predictive control

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Area of Science:

  • Control Engineering
  • Cybersecurity
  • Optimization Theory

Background:

  • Networked control systems are vulnerable to sophisticated deception attacks.
  • Existing methods often struggle with unknown-bounded stochastic attack signals.

Purpose of the Study:

  • To design an innovative security control methodology for linear networked control systems (LNCS) under stochastic deception attacks.
  • To mitigate conservatism in security control design by employing chance constraints.

Main Methods:

  • Introduced an ambiguity set to characterize potential deception signals using mean-covariance constraints.
  • Formulated chance constraints on system state and control variables.
  • Applied distributionally robust optimization for a deterministic convex reformulation.
  • Utilized stochastic model predictive control (SMPC) for recursive feasibility and convergence.

Main Results:

  • Successfully addressed unknown-bounded stochastic deception attacks.
  • Mitigated conservatism in security control design.
  • Demonstrated recursive feasibility and convergence of the controlled system.
  • Validated the approach's superiority through simulations on a DC-DC boost converter.

Conclusions:

  • The proposed security control methodology effectively enhances the resilience of LNCS against stochastic deception attacks.
  • The integration of ambiguity sets, chance constraints, and SMPC offers a promising direction for robust control system design.