Switching Event-Triggered Adaptive Resilient Dynamic Surface Control for Stochastic Nonlinear CPSs With Unknown Deception Attacks

Niu, Ben; Chen, Wendi; Su, Wei; Wang, Huanqing; Wang, Ding; Zhao, Xudong

doi:10.1109/tcyb.2022.3209694

Cited by 29 publications

(15 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Theorem 1. For the system (1) under deception attacks, based on Assumptions 1 and 2 and Lemmas 1 and 2, the presented adaptive secure control scheme consisting of the filter compensators (5), the attack compensators (17), (30) and (47), the virtual controllers (19) and (29), the adaptive laws (18), (31), and (48), the controller (46), can ensure the following properties hold.…”

Section: F I G U R Ementioning

confidence: 99%

“…Deception attacks, as one of the malicious attack manners, change the authenticity of the transmitted signals by injecting false data into sensors or actuators to paralyze a system. [16][17][18][19] Therefore, how to maintain the stability of the system under cyber attacks has emerged as an important research topic. In Reference 20, an adaptive formation control scheme for linear systems was developed to cope with deception attacks.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Event‐based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation

Cao,

Niu,

Wang

et al. 2024

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

This paper investigates an event‐triggered adaptive resilient control problem for nonlinear systems against unknown false data injection and actuator saturation. The sensors of the controlled system are subject to unknown false data injection attacks so that all original states can not be directly applied in the controller design process. To address the negative effects of the false data injection attacks, attack compensators are introduced in control design. Simultaneously, a dynamic event‐triggering mechanism is set up to reduce the communication burden of the network. Furthermore, an auxiliary system is constructed to cope with the actuator saturation that commonly exists in practical systems. Based on the Lyapunov stability theory, it is demonstrated that the designed adaptive controller can guarantee the stability of the controlled system and the boundedness of all signals. The validity of the proposed control scheme is evidenced by simulation examples.

show abstract

Section: F I G U R Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Event‐based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation

Cao,

Niu,

Wang

et al. 2024

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

show abstract

“…In recent years, SSs have received much attention due to their increasingly wide application prospects in robotic systems, power systems, aircraft systems and chemical reaction systems, etc. (see References 1–6). It is worth noting that due to the disturbance of the external environment and the uncertainty of the system parameters, it often leads to random switching between subsystems.…”

Section: Introductionmentioning

confidence: 99%

Stabilization and destabilization of impulsive Markovian switching systems via periodic stochastic controls and impulsive controls

Liu,

Cheng,

Cui

2023

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

Given an unstable (or stable) impulsive Markovian switching system (IMSS), can it be stabilized (or destabilized) by noise? This problem has not been studied. In view of this question, this article will establish the noise stabilization and destabilization strategies of IMSS, and also study the impulsive control realized by adjusting the impulse intensity. It is worth noting that the impulse jump is the random impulse whose jump value depends on the mode, and the noise stabilization and destabilization are realized by periodic stochastic control based on Lévy noise. In order to establish these new results, we use the time‐inhomogeneous property of coefficients of the controlled system and the ergodicity of discrete‐time Markov chains based on impulse trigger time. In addition, the periodic stochastic control on diffusion and jump terms can be applied to design intermittent stochastic control.

show abstract

“…In [18], a novel coordinate transformation technology was proposed, aiming to achieve tracking control for the attacked CPS. There is also a part of the literature that considers CPS subject to stochastic disturbances and network attacks [19][20][21][22][23][24]. For example, an innovative distributed adaptive control strategy is developed in [19] for networked multi-agent systems against sensor and actuator attacks, as well as stochastic disturbances.…”

Section: Introductionmentioning

confidence: 99%

Output Feedback Adaptive Inverse OptimalSecurity Control for Stochastic NonlinearCyber-Physical Systems under Sensor andActuator Attacks

Chen,

Yu,

2024

Preprint

View full text Add to dashboard Cite

This paper addresses the inverse optimal security control problems for a class of stochastic non-strict feedback nonlinear Cyber-Physical Systems under sensor and actuator attacks. The concerned system model includes both stochastic disturbances and more general nonlinearity. First, to make the control design feasible, a linear state transformation is applied to the attacked system. Furthermore, in the process of backstepping design, based on the Nussbaum gain function formula, fuzzy logic system approximation method, and inverse optimal control theory, combing the available output signal, an output feedback inverse optimal controller is proposed. Specifically, the designed controller not only ensures that the system is secure under network attacks but also optimal in terms of the cost function. Finally, two physical examples are given to verify the effectiveness of the proposed control scheme in various network attacks.

show abstract

Switching Event-Triggered Adaptive Resilient Dynamic Surface Control for Stochastic Nonlinear CPSs With Unknown Deception Attacks

Cited by 29 publications

References 25 publications

Event‐based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation

Event‐based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation

Stabilization and destabilization of impulsive Markovian switching systems via periodic stochastic controls and impulsive controls

Output Feedback Adaptive Inverse OptimalSecurity Control for Stochastic NonlinearCyber-Physical Systems under Sensor andActuator Attacks

Contact Info

Product

Resources

About