Adaptive fault-tolerant control for nonlinear multi-agent systems with DoS attacks

Zhao, Liang; Yang, Guang‐Hong

doi:10.1016/j.ins.2020.03.083

Cited by 72 publications

(32 citation statements)

References 34 publications

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“…The data link under C-C DoS attack is shown in Figure 9, which yellow lightning symbols denotes the links be cut off in first DoS attack and red lightning symbols denotes the second time. The first DoS attack is active during the time interval [10,15] [sec], and the second wave is active during the time interval [15.5,25] [sec]. Case 3 simulation result is shown in Figures 10-12.…”

Section: Casementioning

confidence: 99%

“…Then Reference 8 extends the DoS attack problem to the S‐C link. Fault‐tolerant control scheme was deployed to handle C‐A fault injection attack, 9,10 the researchers also designed monitor and switching mechanism to engage C‐C link DoS attacks. In Reference 11, the fault injection and DoS attack on C‐C links of high‐order MAS scaled group consensus problem is studied, but the controller design process is complicated.…”

Section: Introductionmentioning

confidence: 99%

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Consensus tracking control for uncertain non‐strict feedback multi‐agent system under cyber attack via resilient neuroadaptive approach

Yang²,

Ma³

et al. 2022

Intl J Robust & Nonlinear

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Multi-agent system (MAS) is a common cyber-physical system (CPS). Due to it often uses a relatively open network platform, it is vulnerable to malicious cyber attacks in the process of system operation, so the control scheme design is critical to ensure the system operation security. In this article, we propose a new resilient neuroadaptive dynamic surface control scheme for non-linear MASs with potential cyber attacks (false data injection and denial-of-service), system uncertainty, unknown control gain, and output constraints which are usually seen on CPSs.In this scheme, the neuroadaptive controller design ensures that all signals of the closed loop system are semi-globally uniform ultimately bounded when the MAS even exists time-varying cyber attacks on data links among agents, and the links between controllers, actuators, and sensors. Using Gaussian radial basis function neural network, the system uncertainty, non-strict feedback terms, unknown control gain, and some cyber attacks are effectively solved and the process of controller design is extremely simplified. Finally, we provide a simulation result to verify the effectiveness and superiority of the proposed control scheme.

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Section: Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Consensus tracking control for uncertain non‐strict feedback multi‐agent system under cyber attack via resilient neuroadaptive approach

Yang²,

Ma³

et al. 2022

Intl J Robust & Nonlinear

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“…In [19], considered the communication network may be attacked in nonlinear networked control systems, a new attack detection and estimation approach based on neural network is presented. The authors in [20] studied the nonlinear multi-agent systems with DoS attacks and actuator faults, where the purpose of adversary is to hinder communication between agents, and a jumping scheme is presented for warranting the tolerance for network Observer-based decentralized fuzzy control for connected nonlinear vehicle systems Meng Li a,* , Yong Chen a , Kun Hu a , Chengwei Pan a , Zhenhai Mao a connection lost. In [21], for nonlinear systems with sensor attacks, for the purpose of solving the problem of state estimation, an estimation method based on multi-observers and sensor redundancy is proposed.…”

Section: Introductionmentioning

confidence: 99%

Observer-based decentralized fuzzy control for connected nonlinear vehicle systems

Chen

et al. 2022

Preprint

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This article analyzes the tracking control of a type of connected nonlinear vehicle system, where the problem of hacker attacks and external disturbance is considered . A decentralized fuzzy control method based on observer is constructed. Specifically, first of all, the mathematical model of an automobile system with disturbance and false data injection attacks is built, which is composed of a head vehicle and N following vehicles. Then, in order to obtain prior knowledge of disturbance and states, a disturbance estimator on fuzzy sliding mode technique is proposed and a state observer is designed. Thirdly, an observer-based decentralized secure control strategy via fuzzy and backstepping control technique is designed to achieve the tracking control. Furthermore, the boundness of closed-loop signals and existence of appropriate safety distance between vehicles are certificated by Lyapunov theory. Finally, the potential of presented approaches are simultaneously illustrated by a numerical simulation and a semi-physical simulation.

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“…Actuator faults become a research topic due to the severe related degradation of global behavior caused by them. [26][27][28] To compensate for the effects of the actuator faults, various types of fault-tolerant control (FTC) methods, such as hierarchical control scheme, 29 decentralized output sliding-mode controller, 30 and distributed learning control approach, 31 are reported in previous kinds of literature. Among them, the distributed controller has drawn wide attention as a promising method to realize the consensus of MASs with four types of actuator faults.…”

Section: Introductionmentioning

confidence: 99%

“…• A fully distributed fault-tolerant consensus tracking control protocol is proposed to improve reliability by the neural network-based adaptive mechanism. Compared with the existing fault-tolerant controllers, 3,[26][27][28][29][30] the proposed controller does not require any knowledge about the terms relevant to the global information associated with the network. Furthermore, the proposed controller can compensate for the leader's unknown bounded input and actuator faults.…”

Section: Introductionmentioning

confidence: 99%

Distributed robust fault‐tolerant consensus tracking control for multi‐agent systems with exogenous disturbances under switching topologies

Sader

Liu

Wang

et al. 2021

Intl J Robust & Nonlinear

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In this article, the H ∞ consensus tracking problem for multi-agent systems (MASs) under switching communication topologies is studied. In the objective system, the unknown nonlinear function, exogenous disturbances, and actuator faults are considered. For this problem, a new fully distributed fault-tolerant control method is developed via utilizing adaptive mechanisms. A sufficient condition is obtained to guarantee the stability of the considered closed-loop system by topology-based average dwell time technique combined with Lyapunov stability theory. Unlike the traditional method to estimate the weight matrix, the neural network is used to estimate the norm of weight vectors. Thus, the difficulty that the unknown nonlinear function cannot be compensated when outage or stuck faults occur in some actuators is solved. Compared with the existing controllers for nonlinear MASs, the proposed controller does not require any knowledge about the terms relevant to the global information associated with the network. Furthermore, the proposed controller can compensate for the leader's unknown bounded input and actuator faults. Besides, the closed-loop system is proven to be stable by the developed controller, and all followers can track the state of the leader. Finally, a numerical simulation is given to validate the effectiveness of the proposed protocol.

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Adaptive fault-tolerant control for nonlinear multi-agent systems with DoS attacks

Cited by 72 publications

References 34 publications

Consensus tracking control for uncertain non‐strict feedback multi‐agent system under cyber attack via resilient neuroadaptive approach

Consensus tracking control for uncertain non‐strict feedback multi‐agent system under cyber attack via resilient neuroadaptive approach

Observer-based decentralized fuzzy control for connected nonlinear vehicle systems

Distributed robust fault‐tolerant consensus tracking control for multi‐agent systems with exogenous disturbances under switching topologies

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