Regular Papers

International Journal of Control, Automation, and Systems 2025; 23(1): 105-114

https://doi.org/10.1007/s12555-024-0117-8

© The International Journal of Control, Automation, and Systems

Resilient Dual-mode Model Predictive Control for Constrained Linear Networked Control Systems With Random DoS Attacks

Li Qiu*, Shaolie Lin, Runjie Chen, Jie Teng, Zongze Wu*, and Marzieh Najariyan

Shenzhen University, Guangdong University of Technology

Abstract

This paper proposes a resilient dual-mode model predictive control (MPC) framework that simultaneously considers system constraints and denial-of-service (DoS) attacks for linear time-invariant networked control systems (NCS). The DoS attacks is random and occurs at the both sensor-to-controller (S − C) communication channel and controller-to-actuator (C − A) communication channel. The MPC can well compensate the effect of the DoS attacks on the constrained system. At the same time, to address the problem of repeated oscillations caused by the inaccurate model near the equilibrium point of the MPC, and to reduce the computational effort, the resilient two-mode MPC is used. To guarantee the stability of NCS, a resilient terminal invariant set based on LMI is designed to ensure that the constrained system remains stable under M consecutive attacks. Finally, numerical simulations are conducted to validate the proposed MPC framework, showing its effectiveness in practical applications.

Keywords Denial-of-service attacks, networked control systems, resilient dual-mode model predictive control, resilient terminal invariant set.

Article

Regular Papers

International Journal of Control, Automation, and Systems 2025; 23(1): 105-114

Published online January 1, 2025 https://doi.org/10.1007/s12555-024-0117-8

Copyright © The International Journal of Control, Automation, and Systems.

Resilient Dual-mode Model Predictive Control for Constrained Linear Networked Control Systems With Random DoS Attacks

Li Qiu*, Shaolie Lin, Runjie Chen, Jie Teng, Zongze Wu*, and Marzieh Najariyan

Shenzhen University, Guangdong University of Technology

Abstract

This paper proposes a resilient dual-mode model predictive control (MPC) framework that simultaneously considers system constraints and denial-of-service (DoS) attacks for linear time-invariant networked control systems (NCS). The DoS attacks is random and occurs at the both sensor-to-controller (S − C) communication channel and controller-to-actuator (C − A) communication channel. The MPC can well compensate the effect of the DoS attacks on the constrained system. At the same time, to address the problem of repeated oscillations caused by the inaccurate model near the equilibrium point of the MPC, and to reduce the computational effort, the resilient two-mode MPC is used. To guarantee the stability of NCS, a resilient terminal invariant set based on LMI is designed to ensure that the constrained system remains stable under M consecutive attacks. Finally, numerical simulations are conducted to validate the proposed MPC framework, showing its effectiveness in practical applications.

Keywords: Denial-of-service attacks, networked control systems, resilient dual-mode model predictive control, resilient terminal invariant set.

IJCAS
January 2025

Vol. 23, No. 1, pp. 1~88

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