The integration of renewable energy sources increases the vulnerability of power systems to cyber-physical threats, particularly denial-of-service (DoS) attacks that exploit transient instabilities caused by renewable generation fluctuations. These attacks disrupt communication channels, leading to cascading frequency deviations and increased risk of system instability. To address this challenge, we propose a multi-layer defense framework integrating attack modeling, adaptive control, and stability guarantees. First, a frequency-driven DoS attack model is constructed by analyzing frequency trends to identify vulnerable regulation periods and support proactive threat prediction. Second, a hybrid information-based reinforcement learning (HIRL) strategy is developed to adaptively optimize transmission intervals under DoS attacks, balancing regulation performance and communication efficiency. Third, a Takagi–Sugeno (T-S) fuzzy load frequency control with virtual synchronous generator (VSG-LFC) scheme is designed to enhance frequency stability through inertia emulation, mitigating both renewable intermittency and attack-induced oscillations. Lyapunov-based stability analysis is conducted to establish theoretical guarantees for the coupled cyber-physical system. Finally, simulation results on the New England 9-bus system demonstrate the effectiveness and practical applicability of the proposed framework, showing superior frequency stability compared to conventional methods.

This article addresses the problem of finite-time filtering for a class of discrete-time Takagi-Sugeno (T-S) fuzzy-model-based networked control systems (NCSs) subject to switching communication channels and cyber attacks. Specifically, the fluctuations of the state estimator gain parameters are taken into account in the design of the filter. Further, cyber attacks are supposed to take place in the communication channel and can modify the sensor signals by injecting false data if an attack is successful. Meanwhile, the transition probability of the Markov process is a switching phenomenon along with the minimum and maximum bounds of the multichannel communication scheme. By employing appropriate Lyapunov–Krasovskii functional along with reciprocally convex approach, a set of sufficient conditions guaranteeing the finite-time mixed$H_\infty$and passivity performance for NCSs are derived in terms of linear matrix inequalities. In the end, two illustrated examples quantify the effectiveness of the proposed analysis and filter design method.

This paper proposes a novel sampled-data platooning control design for a group of connected autonomous vehicles based on vehicle position sensor measurements, subject to unknown dynamics, leader vehicle control input and interchange cyber-attacks. Considering the limitations of velocity and acceleration sensors, the system approximates the finite difference values of current and recent previous vehicle position measurements. First, a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles, where inter-vehicle information is propagated via a wireless communication network. Second radial basis function neural network-based observer is constructed to estimate the effect unknown dynamics behavior. Third, multiple sampled-data control loops are considered, utilizing a shared communication network for data transmission. Fourth, the overall closed-loop platooning error system is formulated with the addressed stochastic interchange attack. The desired inter-vehicle stability criterion for the closed-loop platoon error system is obtained by employing Lyapunov-Krasovskii stability theory, and the maximum allowable sampling period with control gains for the addressed control problem are determined. Finally, simulation results are presented to substantiate the effectiveness and advantages of the proposed memory sampled-data platooning control algorithm against interchange attacks and leader vehicle input. Additionally, the effect of interchange attacks is compared with DoS attacks.

In this study, combined problem of robust output tracking and disturbance rejection for nonlinear semi-Markovian jump systems with time-varying delays and uncertainties is investigated in through improved-equivalent-input-disturbance-estimator (IEIDE)-based modified repetitive control (MRC) law. More precisely, IEIDE is introduced into the channel of control input to estimate and compensate the disturbance signals with high precision with an eye to attain the robust tracking performance. Subsequently, MRC block is internally embedded in the control loop that makes the system output signals to track the given reference signals inside the selected neighborhood of the equilibrium via repetitive learning. Furthermore, to obtain the controller and observer gain matrices , the linear matrix inequality conditions are derived based on the technique of Lyapunov stability . Finally, a switching boost converter circuit and single-link robot arm model are used to demonstrate the control scheme's efficiency and superiority. In addition to that the comparative study with the existing works are carried out. In this way, the potential benefits from practical perspectives of the developed results are validated.

Abstract This paper focuses on the global asymptotic stability (GAS) problem for Takagi–Sugeno (T-S) fuzzy quaternion-valued bidirectional associative memory neural networks (QVBAMNNs) with discrete, distributed and leakage delays by using non-separation method. By applying T-S fuzzy model, we first consider a general form of T-S fuzzy QVBAMNNs with time delays. Then, by constructing appropriate Lyapunov–Krasovskii functionals and employing quaternion-valued integral inequalities and homeomorphism theory, several delay-dependent sufficient conditions are obtained to guarantee the existence and GAS of the considered neural networks (NNs). In addition, these theoretical results are presented in the form of quaternion-valued linear matrix inequalities (LMIs), which can be verified numerically using the effective YALMIP toolbox in MATLAB. Finally, two numerical illustrations are presented along with their simulations to demonstrate the validity of the theoretical analysis.

This article investigates the asymptotic stabilization of periodic piecewise time-varying systems with time-varying delay under various cyber attacks, particularly deception and acrlong DoS attacks. The addressed system is reformed into a number of time-varying subsystems based on the time interval for each period. Following that, a state-feedback controller with periodic time-varying gain parameters is developed to solve the stabilization problem. The control design depicts the possibility of the aforementioned cyber attacks with two mutually exclusive stochastic Bernoulli distributed parameters. Then, an augmented Lyapunov-Krasovskii functional with periodically varying matrices is used to determine the conditions for designing the proposed controller that ensures the mean-square asymptotic stability of the addressed system. The results of numerical examples support the conclusion that the proposed method is effective and superior, regardless of the cyber attacks involved.

This paper is devoted to designing anH∞fuzzy controller for nonlinear singularly perturbed systems (SPSs) with limited communication bandwidth and parameter uncertainty. The challenges lie in designing a scheduling protocol for slow and fast system dynamics with less conservatism and addressing the issues of mismatched membership functions. The main contributions of this paper are threefold: (1) First, an asynchronous weighted try-once discard (AWTOD) mechanism is designed for slow and fast dynamics to effectively schedule data communication between sensors and the controller. (2) Then, slow and fast controllers are designed using interval type-2 (IT2) fuzzy technique to deal with system nonlinearity and parameter uncertainty. (3) Finally, a composite controller is designed to ensure the asymptotic stability of nonlinear SPSs. The feasibility of our approach is illustrated through a numerical example.

This paper focuses on distributed sliding-mode consensus tracking control of fuzzy multi-agent systems (MASs) under time-varying transmission delays and hybrid cyber-attacks, including deception and denial-of-service (DoS) attacks. Impulsive and switching signals are adopted to describe the dynamic process of the fuzzy MAS subject to hybrid cyber-attacks. In order to address the hybrid cyber-attacks, a novel integral-type sliding surface function grounded on lumped consensus tracking errors is presented, and a resilient control scheme based on this surface is designed accordingly. By adopting the analysis method of hybrid systems and finite-time control theory, sufficient conditions are deduced to guarantee that the tracking error dynamics can achieve the intended sliding surface in a finite time and remain on the surface thereafter. Meanwhile, the quantitative relationships between the influence of hybrid cyber attacks on the convergence rate of the control strategy are clearly revealed. Moreover, the stabilities of the corresponding sliding mode dynamics are investigated. Finally, the example of cooperative fuzzy robot manipulators is used to illustrate the effectiveness and validity of the proposed theoretical results.

This short paper addresses the challenge of network congestion in T-S fuzzy networked control systems (NCSs) caused by denial of service (DoS) attacks and quality of service (QoS) queuing mechanisms. Firstly, a novel signal compression mechanism is introduced to mitigate network congestion. The trigger threshold is optimized using a mini-batch descent gradient algorithm, effectively reducing bandwidth utilization. Furthermore, tailored Lyapunov-Krasovskii functions (LKFs) are established for the system, and we propose an intelligent event-triggered controller (IETC) under machine learning supervision. Finally, the effectiveness of the proposed approach is demonstrated through rigorous verification on the joint CarSim-Simulink platform.

This paper studies the secure sampled-data consensus of multi-agent systems (MASs) under asynchronous independent deception attacks and multiplicative control gain disturbances by developing the looped Lyapunov-Krasovskii functional (LKF) approach. Because of the openness and shareability of communication network, as well as the time delay in the process of data transmission, two independent deception attacks with asynchronous phenomenon are considered in the sensor-to-controller (SC) and controller-to-actuator (CA) channel of MAS communication network. Furthermore, a coupled memory-based sampled-data control scheme is proposed and fractional-delay states on sampling intervals are introduced to construct an improved delay-dependent looped LKF. Therefore, a relaxed condition with lower conservatism is established to asymptotically ensure the secure sampled-data consensus of MASs in mean square under our designed control protocol. Finally, a simulation test applied to unmanned surface vehicles is conducted to validated the performance of designed control strategy.

This article is concerned with the fixed-time stability (FTS) problem of nonlinear impulsive systems (NISs). By means of the impulsive control mechanism and Lyapunov functions theory, several sufficient conditions are established to ensure the FTS of general NISs. Meanwhile, some novel impulse-dependent settling-time estimation schemes are developed, which fully considers the influence of stabilizing impulses and destabilizing impulses on the convergence rate of the system states. The proposed schemes establish a quantitative relationship between the upper bound of the settling time and impulse effects. It shows that stabilizing impulses can accelerate the convergence rate of the system states and leads to the upper bound of the settling time being smaller. Conversely, destabilizing impulses can reduce it and make the upper bound of the settling time larger. Then, the theoretical results are applied to delayed inertial neural networks (DINNs), where two kinds of controllers are designed to realize fixed-time synchronization of the considered systems in the impulse sense. Finally, some numerical examples are provided to illustrate the validity of the proposed theoretical results.

This paper studies the secure aperiodic sampling control issue for Micro-Grids(MGs) under abnormal deception cyber attacks (ADCAs). Firstly, a novel relaxed condition that depends on the time delay (TD) is constructed, further reducing the existing constraint condition. Secondly, a new bilateral delay-dependent looped-functional (BDDLF)$V_{c}(x_{t})$is developed. Thirdly, based on the characteristics of the aperiodic sampling control, another improved BDDLF$V_{d}(x_{t})$is developed for acquiring more state information. Furthermore, an optimized control algorithm is designed using proper integral inequalities and the convex combination method. Then, a new secure aperiodic sampled data (SASD) controller under ADCAs is achieved to guarantee real power-sharing between distributed generators (DGs) and energy storage systems (ESSs) in MG. Finally, simulation experiments are carried out on MG to verify the effectiveness and feasibility of the designed control algorithm.

The prime purpose of this study is to design an output tracking control law in the perspective of compensating the effects induced by time-varying input delays and disturbances. In particular, the control protocol is developed for nonlinear systems, where the nonlinearities are effectively represented as a convex summation of linear subsystems using membership functions, which is precisely referred by fuzzy model approach. Accordingly, with the aid of parallel distributed compensation strategy and extended Smith predictor approach, the fuzzy-dependent dynamic control law is formulated. Moreover, the improved-equivalent-input-disturbance estimator approach is implemented to estimate the disturbance signals, whose output is tied to the resultant dynamic output feedback controller. On such circumstances, the controller gain matrices that assure the asymptotic tracking performance of the addressed system are calculated by solving the derived set of sufficient conditions. Conclusively, the effectiveness of the developed theoretical outcomes is validated by virtue of numerical simulations.

In this article, we focus on the event-triggered observer-based fuzzy positioning control and$L_{2}$-gain analysis of nonlinear unmanned marine vehicle (UMV) systems in network environments, which is subject to a hybrid attack consisting of denial-of-service attack and deception attack. First, based on the Tagaki-Sugeno fuzzy modeling method, a unified switched system model is established for the positioning control of nonlinear UMV systems with actuator saturation, multiplicative gain uncertainties, external disturbance, and hybrid attacks. Then, by resorting to introducing the integral-type state error, a novel adaptive memory-based event-triggered mechanism is proposed to lighten the communication load in UMV systems. Furthermore, a sufficient criterion is proposed to make the mean square exponential stability of UMV systems with a nonweighted$L_{2}$-gain level be guaranteed, and gain parameters of the designed controller and observer are also solved efficiently. Finally, the simulation example demonstrates the effectiveness of the proposed nonfragile control strategy.

Quantized antidisturbance control design problem is presented for a class of interval type-2 (IT2) fuzzy stochastic systems subject to time delays and multiple disturbances. The inherent uncertain nonlinear and hybrid characteristics of the concerned system make it difficult to design a stable antidisturbance controller. In order to properly reflect the characteristics of IT2 fuzzy stochastic models with multiple disturbances, a new fuzzy disturbance observer is proposed to estimate the disturbances generated by a fuzzy exogenous system. Furthermore, a quantized fuzzy antidisturbance control scheme is synthesized by fusing the estimation of the multiple disturbances. With the support of Lyapunov functional method,$It{\hat{o}}$’s formula and auxiliary function-based integral inequality, the resulting IT2 fuzzy stochastic systems are proved to be robustly stochastically stable with mixed$H_\infty$/passivity performance index. The design methods of the fuzzy disturbance observer and quantized antidisturbance controller are formulated in the form of linear matrix inequalities so that the corresponding gain matrices can be easily obtained. Finally, simulation studies on three examples are provided to justify the efficiency of the designed control strategy.

This article addresses the issue of input–output finite-time stabilization for interval type-2 fuzzy systems in the presence of deception attack effects. Our main goal is to make efficient use of network resources by developing an event-triggered controller for interval type-2 fuzzy systems. For the stabilization process, an event-triggered controller that does not share the same membership functions as the system is designed by using affine transformation parameters. Following that, by using an asymmetric Lyapunov–Krasovskii functional and some advanced integral inequalities to establish the sufficient conditions for the existence of the proposed controller. Furthermore, an asymptotic stabilization result is presented and discussed in a comparative analysis as a special case. Due to the asymmetric Lyapunov–Krasovskii functional structure, the transmission delay interval is large compared with some recent studies. Finally, two simulation examples are carried out and the efficiency of designed controller is verified.

This article proposes an improved security-based event-triggered fuzzy control (ETFC) method for studying the asymptotic stability problem of nonlinear networked control systems (NCSs) under denial-of-service (DoS) attacks. The nonlinear NCSs are linearized using the central mean fuzzy method to obtain Takagi-Sugeno (T-S) fuzzy NCSs. Lyapunov–Krasovskii functionals (LKFs) with nonlinear problems are constructed based on fuzzy membership functions. A relaxed condition including nonlinear parameters is given, which considers the nonlinear optimization problem and reduces the positive-definiteness constraint problem of LKFs. An improved double-closed delay correlation function is constructed to obtain more sampling information. Furthermore, a quadratic scaling method is used to obtain a tighter upper bound, making the criterion less conservative. A DoS attack causes the channel's throughput to drop and collapse. Thus, in this article, we design ETFC based on the improved descent gradient algorithm to ensure the communication security of the helicopter system (HS). Finally, the communication security and stability of HS are verified using the Simulink platform.

In this article, a synchronization method of complex dynamical networks (CDNs) with time-varying delay feedback control is proposed to secure communication between the command system and each node of CDNs. To advance the security of the communication between the command system and each node of CDNs, the original information signal transmitted from the command system is encrypted with the techniques of$\mathcal {N}$-shift cipher and public key. Based on the Lyapunov stability sense and linear matrix inequality (LMI) framework, a new delay-dependent synchronization criterion is established to restore the original information signal on each node of the CDN as well as to ensure stable synchronization for secure communication of all nodes of the command system and CDN. With the support of numerical simulation, the validity of the proposed method is verified.

This article aims to resolve the event-based finite-time dissipative filtering issue for interval type-2 fuzzy complex dynamical networks with coupling delays and cyber attacks. An event-triggered scheme introducing the estimation error is designed, which is a tradeoff between state estimator performance and network communication bandwidth in accordance with the practical requirements. Moreover, the cyber attack model is established, which consists of randomly occurring deception attacks. The stochastic variable obeying the Bernoulli distribution is utilized to describe the attack condition. Through handling the linear matrix inequalities (LMIs) with some slack matrices, the event-triggered finite-time filter is designed to guarantee that the resulting systems are finite-time bounded and strictly dissipative. The proposed filter design parameters are obtained by solving LMIs. Finally, a numerical example and a practical example of a tunnel diode circuit system are used to show the effectiveness and applicability of the proposed event-based dissipative filtering scheme.

This article proposes three new methods to enlarge the feasible region for guaranteeing stability for generalized neural networks having time-varying delays based on the Lyapunov method. First, two new zero equalities in which three states are augmented are proposed and inserted into the results of the time derivative of the constructed Lyapunov-Krasovskii functionals for the first time. Second, inspired by the Wirtinger-based integral inequality, new Lyapunov-Krasovskii functionals are introduced. Finally, by utilizing the relationship among the augmented vectors and from the original equation, newly augmented zero equalities are established and Finsler's lemma are applied. Through three numerical examples, it is verified that the proposed methods can contribute to enhance the allowable region of maximum delay bounds.

The issues of input–output finite-time stability and stabilization of Takagi–Sugeno (T–S) fuzzy systems with time-varying state delay and exogenous input signal are studied in this article. For the stabilization process, a controller that does not share the same membership functions as the system is considered and the state feedback is quantized by using a logarithmic quantizer. The desired stability criterion for the addressed fuzzy system is first derived without the control term. It is then extended to the case in which the proposed controller is present. The stability criteria are given in the form of matrix inequalities, which are supported by the augmented Lyapunov–Krasovskii functional, generalized free-weighting-matrix approach and Finsler’s lemma. Moreover, as a special case, an asymptotic stability criterion is obtained and used in a comparative study. As a result, the time-delay interval is much larger than some of the works published very recently, which is due to the augmented Lyapunov–Krasovskii functional construction. In addition, the effectiveness and practicability of the theoretical findings are validated with simulation examples.

In this article, the robust asynchronous filtering problem is investigated for a class of discrete-time T–S fuzzy complex dynamical networks subjected to random coupling delays and deception attacks. Specifically, the deception attacks are considered in the filter, where the adversary attempts to inject some false information data in the measurement output to modify the transmitted signal in the communication networks. We introduce, respectively, two sets of stochastic variables satisfying the Bernoulli distribution to depict the probability of the data transmitted by the network being subjected to time-varying coupling delays and deception attacks. By using Lyapunov–Krasovskii stability theory and Abel lemma-based finite-sum inequality, a new set of sufficient conditions is established, which ensures the stochastic stability of the resulting error system with a prescribed mixed$H_\infty$and passivity performance index. The proposed filter parameters are obtained by solving linear matrix inequalities. Ultimately, both the effectiveness and advantages of the proposed asynchronous filter with deception attacks are verified by two numerical examples including a tunnel diode circuit model.

In this work, the problem of fault and state estimation is studied for Takagi–Sugeno fuzzy systems with time-varying delay and external disturbance over a finite horizon. A fuzzy rule-based fault estimator with two tuning parameters, including the current system output information, is designed. Based on which, the Luenberger state observer is then considered to estimate the immeasurable states of the system addressed. The aim of taking into account the tuning parameters in the estimator design is to improve the accuracy of the fault estimation. More precisely, by defining error variables in accordance with actual and estimated system states and faults, an augmented system is formulated to achieve the desired results. By using the existing stability theory and integral inequality, a delay-dependent criterion for ensuring that the states of the augmented system are bounded over a finite horizon is derived. Subsequently, conditions for determining the observer gain matrices are presented. Two simulation examples, including an application example of the truck-trailer model, are provided to demonstrate the advantages of the theoretical results that have been established. In particular, the importance of the use of tuning parameters is discussed.

The aim of this article is to analyze the problem of fault estimation for mode-dependent interval type-2 fuzzy systems with quantized output measurements. Different from the existing fault estimation methods requiring the observer matching condition, a new fault estimation technique is proposed, wherein a stochastically intermediate variable subject to the information on operating modes is considered, under which a robust observer is constructed to simultaneously estimate the state and faults. Based on the strategy of linear matrix inequality, sufficient conditions are established to ensure that the states of resulting systems are bounded in probability sense. By offering three illustrative examples, in which two of them are practical models, namely, tunnel diode circuit system and Rössler system, the availability and feasibility of the proposed design method are explained.

This article intends to provide an integrated robust synchronization and anti-disturbance control design for a nonlinear multiweighted complex network with the use of fuzzy modeling approach. The network takes the effect of both matched and mismatched disturbances into account, wherein the matched one is unknown and caused by some exogenous systems. In order to estimate the unknown disturbance, a disturbance observer is precisely considered. By exploiting the parallel distributed compensation strategy and the output of disturbance observer, the desired fuzzy rule-based control law is formulated. Based on these settings, the required control gain matrices that affirm asymptotic synchronization of the addressed network are determined with the support of the Lyapunov functional method and extended Wirtinger's integral inequality. The method of this article can render better system performance than the existing H∞control method, which is demonstrated via simulations. In addition, a three-dimensional Lorenz chaotic model is employed to certify the applicability of the theoretical findings.

This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

This paper designs a new leader-following consensus protocol for second-order multiagent systems with time-varying sampling. For the first time in designing a leader-following protocol, the concept of betweenness centrality is adopted to analyze the information flow in the consensus problem for multiagent systems. By construction of a suitable Lyapunov-Krasovskii functional, some criteria for designing consensus protocols of such systems are established in terms of linear matrix inequalities which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the validity of the proposed argument.

This paper proposes new stability and stabilization conditions for discrete-time fuzzy systems with time-varying delays. By constructing a suitable Lyapunov-Krasovskii functional and introducing a new summation inequality based on the inequality of Cauchy-Schwartz form, which enhances the feasible region of the stability criterion for discrete-time systems with time-varying delay, a stability criterion for such systems is established. In order to show the effectiveness of the proposed inequality, which provides more tight lower bound of a summation term of quadratic form, a delay-dependent stability criterion for such systems is derived within the framework of linear matrix inequalities, which can be easily solved by various effective optimization algorithms. Going one step forward, the proposed inequality is applied to a stabilization problem in discrete-time fuzzy systems with time-varying delays. The advantages of the proposed stability and stabilization criteria are illustrated via two numerical examples.

In this brief, an extended dissipativity analysis was conducted for a neural network with time-varying delays. The concept of the extended dissipativity can be used to solve for the H∞, L2-L∞, passive, and dissipative performance by adjusting the weighting matrices in a new performance index. In addition, the activation function dividing method is modified by introducing a tuning parameter. Examples are provided to show the effectiveness and less conservatism of the proposed method.

This paper considers the problem of delay-dependent stability criteria for neural networks with time-varying delays. First, by constructing a newly augmented Lyapunov-Krasovskii functional, a less conservative stability criterion is established in terms of linear matrix inequalities. Second, by proposing novel activation function conditions which have not been proposed so far, further improved stability criteria are proposed. Finally, three numerical examples used in the literature are given to show the improvements over the existing criteria and the effectiveness of the proposed idea.