Model Predictive Control for Networked Multiple Linear Motors System Under DoS Attack and Time Delay

Li, Qiu; Dai, Longcheng; Ahsan, Usama; Chen, Fang; Najariyan, Marzieh; Pan, Jianfei

doi:10.1109/tii.2021.3139127

Cited by 25 publications

(3 citation statements)

References 30 publications

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“…In Jiang et al (2020), it is shown that the delay in impulses has double effects, that is, it can stabilize an unstable system or destroy a stable system under the corresponding conditions. When the time delay is within the specified upper and lower bounds, Qiu et al (2023) provide the conditions for the system to achieve consensus against DoS attacks. Although both attacks and time delays are considered in the literature mentioned above, it should be pointed out that the attacks occured are synchronized for all the nodes or edges.…”

Section: Introductionmentioning

confidence: 99%

Consensus of impulsive coupled networked delay systems under edge-based attacks

Zhang,

Li,

Sun

2023

Transactions of the Institute of Measurement and Control

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This paper investigates the consensus of impulsive coupled networked delay systems (NDSs) under edge-based attacks. First, an edge-based attack model is established, which is asynchronous and can change the states of nodes. Next, according to the number of edges allowed to be attacked at a time instant, the edge-based attack is divided into two cases. For each case, the sufficient condition is given to guarantee the system consensus against the edge-based attacks. Then, by considering a special type of edge-based attacks on the NDSs with star topology, a less conservative consensus criterion is obtained. Finally, two numerical examples are given to verify the correctness of the obtained results.

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Section: Introductionmentioning

confidence: 99%

Consensus of impulsive coupled networked delay systems under edge-based attacks

Zhang,

Li,

Sun

2023

Transactions of the Institute of Measurement and Control

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“…To achieve optimal control of constrained UAVs, 21 proposed an algorithm based on MPC and uses an ant colony algorithm to accelerate the solution process of MPC. 22 proposed an MPC network control strategy to efficiently handle the negative effect of time delays and attacks in S-C communication channels on multi-motors. In 23 , a resilient MPC strategy is formulated for CPS subject to false data injection while constrained.…”

Section: Introductionmentioning

confidence: 99%

Resilient dual-mode model predictive control for constrained linear networked control systems with random DoS attacks

Wu,

Qiu,

Lin

et al. 2023

Preprint

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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.

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“…On the other hand, security control under DoS attacks has been drawing increasing attentions in recent years (D. Zhang, Wang, Feng, Shi, & Vasilakos, 2021). For instance, the work presented in (Qiu et al, 2021) uses model predictive control to ensure the uniform global asymptotic stability of a networked multiple linear motors system under DoS attacks and time delays. In (D. Zhang, Shen, Zhou, Dong, & Yu, 2021), a switched time-delay system model is developed to guarantee the exponential platooning tracking of connected vehicles with DoS attacks and nonuniform sampling.…”

Section: Introductionmentioning

confidence: 99%