Event-Based Impulsive Control of IT2 T–S Fuzzy Interconnected System Under Deception Attacks

Rong, Nannan; Wang, Zhanshan

doi:10.1109/tfuzz.2020.2983904

Cited by 35 publications

(21 citation statements)

References 52 publications

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“…Literature [ 22 ] assumes that the process of packet loss obeys independent distribution, analyzes the influence of packet loss rate on the dynamic performance of single-input single-output control system by power spectral density method, and gives the upper bound of data loss rate to maintain certain dynamic characteristics. As per literature [ 23 ], under the constraint of information rate, the stability of WNCS with time-varying transmission period is studied, the sufficient conditions to ensure the stable transmission period of the system are derived, and the upper bound of the transmission period is determined by the exhaustive method. Literature [ 24 ] proposed a dynamic programming method in the process of solving multilevel decision-making problems.…”

Section: Related Workmentioning

confidence: 99%

Optimal Control of Whole Network Control System Using Improved Genetic Algorithm and Information Integrity Scale

2022

Computational Intelligence and Neuroscience

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WNCS (Whole network control system) is a network-based distributed control system. The control loop formed by the serial network usually includes several subcontrol systems. WNCS optimal control is a complex and multiparameter coupled highly nonlinear system. Combining the advantages of GA (genetic algorithm), neural network, and fuzzy control, a WNCS optimal control method based on improved GA is proposed. This scheme has both the strong global searching ability of GA and the robustness and self-learning ability of neural network. The simulation results show that the algorithm can keep the diversity of population genes and effectively restrain the premature convergence of the algorithm. On this basis, the optimal control problem of WNCS with short time delay with information integrity scale is studied. The model transformation is used to transform the long time-delay system into a formal nondelay nonlinear system, and then the transformed nondelay nonlinear system obtains the optimal control law that meets the infinite time-domain quadratic performance index without considering packet loss by successive approximation method. The simulation results verify the effectiveness and correctness of the compensation algorithm for nonlinear WNCS.

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Section: Related Workmentioning

confidence: 99%

Optimal Control of Whole Network Control System Using Improved Genetic Algorithm and Information Integrity Scale

2022

Computational Intelligence and Neuroscience

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“…A j = P 2 Âj P −1 3 P T 2 , B j = P 2 Bj , C j = Ĉj P −1 3 P T 2 , D j = Dj P −1 3 P T 2 . Bringing them into Equations ( 20)-( 22), we can obtain Equations ( 33)- (35). By using Schur Complement Lemma, the matrix P is equivalent to P 1 − P 2 P −1 3 P T 2 = P 1 − Y > 0.…”

Section: Fault Diagnosis Filter Designmentioning

confidence: 99%

“…When this issue is considered, the general T-S fuzzy modeling scheme cannot achieve the desired results [15]. The IT2 fuzzy model was developed because of its good proxy for nonlinear systems with parameter uncertainty [29][30][31][32][33][34][35][36][37]. The problem of the FD filtering method is proposed with event-based, which is the application in IT2 fuzzy theory under the framework of networked timedelay control systems [29].…”

Section: Introductionmentioning

confidence: 99%

“…The nonlinear networked system with parameter uncertainty is studied under the eventtriggered mechanism with adaptive discrete H ∞ fuzzy filtering described by IT2 T-S fuzzy model [32]. In [33][34][35][36][37][38], the FD fighting design, impulse control and discrete control based on the IT2 fuzzy model are studied. Interval two-type theory is being recognized and studied by more and more scholars [39,40].…”

Section: Introductionmentioning

confidence: 99%

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Fault Detection for Interval Type-2 T-S Fuzzy Networked Systems via Event-Triggered Control

Zhang

Fei

et al. 2022

Machines

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This paper investigates the event-triggered fault diagnosis (FD) problem for interval type-2 (IT2) Takagi–Sugeno (T-S) fuzzy networked systems. Firstly, an FD fuzzy filter is proposed by using IT2 T-S fuzzy theory to generate a residual signal. This means that the FD filter premise variable needs to not be identical to the nonlinear networked systems (NNSs). The evaluation functions are referenced to determine the occurrence of system faults. Secondly, under the event-triggered mechanism, a fault residual system (FRS) is established with parameter uncertainty, external disturbance and time delay, which can reduce signal transmission and communication pressure. Thirdly, the progressive stability of the fault residual system is guaranteed by using the Lyapunov theory. For the energy bounded condition of external noise interference, the performance criterion is established using linear matrix inequalities. The matrix parameters of the target FD filter are obtained by the convex optimization method. A less conservative fault diagnosis method can be obtained. Finally, the simulation example is provided to illustrate the effectiveness and the practicalities of the proposed theoretical method.

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“…Compared to the aforementioned two forms of cyber-attacks, the deception attack is difficult to detect and prevent [48]. Therefore, much effort has been devoted to alleviating the negative impacts from deception attack, and great progress has been made in recent years [49][50][51][52].…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Formation Tracking Control for Unmanned Aerial Vehicles Subjected to Deception Attacks

Biao

Xiong

2021

Electronics

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This study investigates the time-varying formation tracking (TVFT) control problem for multiple unmanned aerial vehicle (multi-UAV) systems under deception attacks by utilizing an event-triggered mechanism (ETM). First, for the sake of alleviating the communication burden, an effective ETM is designed in this paper. Second, to deal with deception attacks in the communication network, a random deception attack model under the designed ETM is constructed. Finally, a novel formation tracking control scheme for multi-UAV systems under deception attack combining the ETM is proposed to achieve the expected TVFT. The stability analysis of the formation control system is given by using the Lyapunov stability theory and linear matrix inequality (LMI) technique. Simulations are conducted to verify the effectiveness of the proposed formation control scheme.

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Event-Based Impulsive Control of IT2 T–S Fuzzy Interconnected System Under Deception Attacks

Cited by 35 publications

References 52 publications

Optimal Control of Whole Network Control System Using Improved Genetic Algorithm and Information Integrity Scale

Optimal Control of Whole Network Control System Using Improved Genetic Algorithm and Information Integrity Scale

Fault Detection for Interval Type-2 T-S Fuzzy Networked Systems via Event-Triggered Control

Event-Triggered Formation Tracking Control for Unmanned Aerial Vehicles Subjected to Deception Attacks

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