Observer-based state feedback<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e1528" altimg="si3.svg"><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:math>control for offshore steel jacket structures under denial-of-service attacks

Cao, En-Zhi; Zhang, Baolin; Cai, Zhihui; Han, Qing‐Long; Wang, Binrui

doi:10.1016/j.isatra.2021.01.006

Cited by 12 publications

(3 citation statements)

References 28 publications

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“…During time

t-\tau

to t time period, the acceleration value cannot reach the actuator on time intervals through the VANET network remains the same. At time

t

, the transmission of the feedforward control signal previously suspended due to the DoS attack begins via a wireless channel 28 . Thus, according to (), the time‐delay acceleration dynamic model can be written as,

$$ {\dot{a}}_i(t)=\frac{k_p{d}_i(t)}{\sigma_i}-\frac{\left({k}_d+{k}_ph\right){v}_i(t)}{\sigma_i}-\frac{\left(1+{k}_dh\right){a}_i(t)}{\sigma_i}+\frac{k_d{v}_{i-1}(t)}{\sigma_i}+\frac{u_{ff,i}\left(t-\tau \right)}{\sigma_i}-\frac{k_p{r}_i}{\sigma_i}+\frac{f_i\left(\bullet \right)}{\left({m}_i{\sigma}_i\right)}.

…”

Section: Problem Statement and Modelingmentioning

confidence: 99%

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An adaptive observer design for denial‐of‐service attack detection in platoon

Zhang

et al. 2023

Optim Control Appl Methods

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Due to the increasing demand for autonomous driving, cyber-attacks detection nowadays receives significant attention. Among several different types of attacks, Denial-of-Service (DoS) attacks can consume resources and cause the system under attack to stop responding, which can be considered a time delay model affecting the response of the attacked system. To detect the possible DoS attacks in Cooperative Adaptive Cruise Control platoon model, an adaptive observer design is proposed in this paper, where the time delay caused by DoS attacks can be fast and accurately estimated. To highlight the performance of the proposed adaptive observer, numerical simulations are applied and the performance is compared against the sliding mode observer in terms of the DoS attack time delay estimation convergence and accuracy.

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“…During time

t-\tau

to t time period, the acceleration value cannot reach the actuator on time intervals through the VANET network remains the same. At time

t

$$ {\dot{a}}_i(t)=\frac{k_p{d}_i(t)}{\sigma_i}-\frac{\left({k}_d+{k}_ph\right){v}_i(t)}{\sigma_i}-\frac{\left(1+{k}_dh\right){a}_i(t)}{\sigma_i}+\frac{k_d{v}_{i-1}(t)}{\sigma_i}+\frac{u_{ff,i}\left(t-\tau \right)}{\sigma_i}-\frac{k_p{r}_i}{\sigma_i}+\frac{f_i\left(\bullet \right)}{\left({m}_i{\sigma}_i\right)}.

…”

Section: Problem Statement and Modelingmentioning

confidence: 99%

“…At time t, the transmission of the feedforward control signal previously suspended due to the DoS attack begins via a wireless channel. 28 Thus, according to (7), the time-delay acceleration dynamic model can be written as,…”

Section: Dos Attack Modelmentioning

confidence: 99%

An adaptive observer design for denial‐of‐service attack detection in platoon

Zhang

et al. 2023

Optim Control Appl Methods

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“…Therefore, it is necessary to carry on research about the attacked NCS. Attacks are divided into two categories, deception attacks [3] and DoS (Denial-of-Service) attacks [4,5,6]. Reference [3] studied the security problem of the NCS under deception attacks, a new estimation method was proposed and the sufficient conditions for the stability of the system were obtained.…”

Section: Introductionmentioning

confidence: 99%

Strong γ_c - γ_cl H_∞ Stabilization for Networked Control System Based on Lyapunov Function and DoS Attacks

Zheng

Zhou

2022

J. Phys.: Conf. Ser.

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This paper is concerned with the strong γc - γcl H∞ stabilization for networked control system under DoS attacks with limited communication bandwidths. The quantizer is employed to the network transmission channel from sensor-to-controller in order to reduce the unnecessary data transmissions. In the network environment, it is assumed that there exist DoS attacks in the transmission channel from controller-to-actuator. By describing DoS attacks as the probability models subject to the Bernoulli distribution, the network control system is modeled as the system with random parameters. With this model, a dynamic output feedback controller is designed, which satisfies the given H∞ bound norm γc . Under the action of the controller, the closed-loop system is exponential stable in the mean-square sense and satisfies H∞ bound norm γcl . Especially, a Lyapunov function based on quantization error and attack probability is proposed in the stability analysis. Finally, the effectiveness of the proposed method is verified by a simulation example.

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H∞$$ {\boldsymbol{H}}_{\mathbf{\infty}} $$ Control With Event‐Triggered Mechanism for T‐S Fuzzy System Under Multiple Cyber‐Attacks

Tan,

Gao,

Guo

2024

Intl J Robust & Nonlinear

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The problem of event‐triggered control for networked Takagi–Sugeno (T‐S) fuzzy system under aperiodic DoS attacks and deception attacks is investigated. First, an event generator is introduced in the Sensor‐to‐Controller channel to determine the transmission of data. At the same time, the Sensor‐to‐Controller channel is assumed to be subjected to deception attacks that are randomly distributed but not Bernoulli distributed. Next, the impact of aperiodic DoS attacks on the Controller‐to‐Actuator channel is further considered, and the DoS attack behavior is described in terms of attack period and frequency. The article designs an adaptive resilience event‐triggered mechanism (ARETM), which is aimed at circumventing the ineffective data updating in the “active” phase of the DoS attacks, thereby realizing the effective saving of communication resources and mitigating the adverse effects of DoS attacks. Then, the switched fuzzy system is established to cope with the different states of the DoS attackers. Using the piecewise Lyapunov function, a design method for the controller gains and the ARETM matrix is obtained, which allows the system to be stabilizable and obtain performance under the control action. Finally, the effectiveness of the ARETM‐based control strategy is confirmed by simulation experiment.

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Observer-based state feedbackH∞control for offshore steel jacket structures under denial-of-service attacks

Cited by 12 publications

References 28 publications

An adaptive observer design for denial‐of‐service attack detection in platoon

An adaptive observer design for denial‐of‐service attack detection in platoon

Strong γ_c - γ_cl H_∞ Stabilization for Networked Control System Based on Lyapunov Function and DoS Attacks

H∞$$ {\boldsymbol{H}}_{\mathbf{\infty}} $$ Control With Event‐Triggered Mechanism for T‐S Fuzzy System Under Multiple Cyber‐Attacks

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Observer-based state feedbackH∞control for offshore steel jacket structures under denial-of-service attacks

Cited by 12 publications

References 28 publications

An adaptive observer design for denial‐of‐service attack detection in platoon

An adaptive observer design for denial‐of‐service attack detection in platoon

Strong γc - γcl H∞ Stabilization for Networked Control System Based on Lyapunov Function and DoS Attacks

H∞$$ {\boldsymbol{H}}_{\mathbf{\infty}} $$ Control With Event‐Triggered Mechanism for T‐S Fuzzy System Under Multiple Cyber‐Attacks

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Product

Resources

About

Strong γ_c - γ_cl H_∞ Stabilization for Networked Control System Based on Lyapunov Function and DoS Attacks