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This article investigates the problem of resilient secure control of cloud-aided 5-DOF active semivehicle suspension systems (SVSSs). A novel joint model considering both the event-triggered mechanism (ETM) and Denial of Service (DoS) attacks is established. Under such a model, during the active period of DoS attacks, periodic transmission attempt is made to ensure the control system can receive the control information at the earliest time; the ETM turns to be a conventional one when the DoS attack is in sleeping period. Meanwhile, the valid attack period is proposed to address the problem of the DoS attack ending within a sampling period, which is a challenging problem in modeling DoS attacks. Takagi–Sugeno (T–S) fuzzy model is used to characterize the uncertainties of sprung and unsprung mass of SVSSs. By converting the cloud-aided active SVSS into a fuzzy-based switched time-delay system, and using the method of piecewise Lyapunov function, sufficient conditions are derived to ensure the performances of active SVSSs subject to DoS attacks. Finally, the effectiveness of the proposed method is validated by a numerical example of active SVSSs subject to DoS attacks. [ABSTRACT FROM AUTHOR]

This paper focuses on the resilient ${H_{\infty }}$ filter design for event-triggered networked systems subject to nonperiodic denial-of-service (DoS) jamming attacks. In this paper, a new resilient event-triggered transmission strategy is first proposed to improve the efficiency of network resource utilization while counteracting the nonperiodic DoS jamming attacks. Then, by using a time-delay approach, the filtering error system is modeled as a switched system, which characterizes the effects of the event-triggering scheme and nonperiodic DoS jamming attacks simultaneously. Based on the established model, by using the piecewise Lyapunov–Krasovskii functional method, linear matrix inequality (LMI)-based sufficient conditions are formulated to achieve the globally exponential stability as well as the weighted ${H_{\infty }}$ performance of the resulting switched system under the DoS jamming attacks. Consequently, the co-design method for the desired filter parameters and event-triggering parameters can be formulated provided that the above LMIs are feasible. Finally, the effectiveness of the proposed method is demonstrated by a practical example. [ABSTRACT FROM AUTHOR]

This paper is concerned with distributed event-triggered consensus of a generally linear multi-agent system subjected to periodic denial-of-service (DoS) jamming attacks. First, a novel switched time-varying delay system model is established to describe consensus error dynamics. By virtue of the switched system and time delay system approaches, one constraint is obtained as a tradeoff between exponential convergence rate of consensus error and uniform lower bound of sleep intervals of periodic DoS jamming attacks. Second, sufficient conditions are derived to guarantee exponential consensus of the multi-agent system. Third, a co-design method is presented to determine the parameters of both the distributed event-triggered mechanism and consensus protocol. Furthermore, an algorithm is given to find the allowable uniform lower bound of sleep intervals and suboptimal distributed event-triggering parameters. Finally, an illustrative example is provided to verify the effectiveness of the proposed resilient event-triggering consensus design method against periodic DoS jamming attacks. [ABSTRACT FROM AUTHOR]

In this paper, an integral reinforcement learning-based value iteration algorithm is developed for solving the infinite horizon optimal tracking control problem of nonlinear continuous-time systems with time delay. The main idea is using the value iteration technique to obtain the iterative control law, which optimizes the iterative performance index function. In contrast to the existing value iteration algorithms, the proposed IRL-based value iteration algorithm takes the time delay into account. Second, the convergence analysis of the proposed algorithm is given for the nonlinear continuous-time systems with time delay. Moreover, the critic neural network is utilized to approximate the performance index function and compute the optimal control law for facilitating the implementation of the iterative algorithm. Finally, the simulation results are presented to illustrate the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

This paper studies an adaptive neural control for nonlinear multiple‐input multiple‐output systems with dynamic uncertainties, hysteresis input, and time delay. The studied systems are composed of N nonlinear time‐delay subsystems and the interconnection terms are contained in every equation of each subsystem. Adaptive neural control algorithms are developed by introducing a well‐defined smooth function. The unknown time‐varying delays and the unmodeled dynamics are dealt with by constructing appropriate Lyapunov–Krasovskii functions and introducing an available dynamic signal. The main advantage of the proposed controllers is that they contain fewer parameter estimates that need to be updated online. Consequently, the accuracy of ultimate tracking errors asymptotically approaches a pre‐defined bound, and all signals in the closed‐loop systems are also ensured to be uniformly ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness and merits of the proposed adaptive neural network control schemes. [ABSTRACT FROM AUTHOR]

Considering interconnections among subsystems, we propose an adaptive neural tracking control scheme for a class of multiple-input-multiple-output (MIMO) non-affine pure-feedback time-delay nonlinear systems with input saturation. Neural networks (NNs) are employed to approximate unknown functions in the design procedure, and the separation technology is introduced here to tackle the problem induced from unknown time-delay items. The adaptive neural tracking control scheme is constructed by combining Lyapunov–Krasovskii functionals, NNs, the auxiliary system, the implicit function theory and the mean value theorem along with the dynamic surface control technique. Also, it is proven that the strategy guarantees tracking errors converge to a small neighbourhood around the origin by appropriate choice of design parameters and all signals in the closed-loop system uniformly ultimately bounded. Numerical simulation results are presented to demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper addresses the model-based event-triggered predictive control problem for networked control systems (NCSs). Firstly, we propose a discrete event-triggered transmission scheme on the sensor node by introducing a quadratic event-triggering function. Then, on the basis of the aforementioned scheme, a novel class of model-based event-triggered predictive control algorithms on the controller node is designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. Two cases, that is, the value of the communication delay of the first event-triggered state is less or bigger than the sampling period, are considered separately for certain NCSs, regardless of the communication delays of the subsequent event-triggered states. The codesign problems of the controller and event-triggering parameter for the two cases are discussed by using the linear matrix inequality approach and the (switching) Lyapunov functional method. Furthermore, we extended our results to the NCSs with systems uncertainties. Finally, a practical ball and beam system is studied numerically to demonstrate the compensation effect for the communication delays with the proposed novel model-based event-triggered predictive control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the decentralized control for a large-scale system with an IP-based communication network. The decentralized controller design specifically takes the nonuniform communication-delay-distribution characteristic of the IP-based communication network into account. First, a networked decentralized control modeling for the large-scale system is proposed. The two main points are: 1) a decentralized controller is designed, which does not depend on the full-order state of the system and 2) the nonuniform communication-delay-distribution characteristic of the IP-based communication network is fully considered in the controller design. Second, if the probability distribution of communication delay is known a priori in the design process, sufficient stability and stabilization conditions for the networked large-scale system are derived in terms of linear matrix inequalities. It shows that, the solvability of the design depends not only on the probability distribution of the communication delay but also on the network topology. Finally, the design method is applied to two pendulums coupled by a spring and a quadruple-tank process. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Abstract: A piecewise analysis method (PAM) is proposed to investigate the performance analysis and control design for nonlinear networked control systems (NNCSs), which are presented in the form of T–S fuzzy model with time-varying input delay. Different from the existing method in dealing with the time-varying delay, the whole variation interval of the delay is divided into two subintervals with equal length. Respecting for the delay belonging each subinterval, new criteria on performance analysis of the NNCSs are obtained by checking the variation of the derivative of the Lyapunov functional in the two subintervals. Then, criteria for the controller design are obtained by using the convexity properties of the matrix inequality and some other new analysis techniques, which are shown in terms of nonlinear matrix inequalities and can be solved by using a cone complementarity liberalization method. As application of the derived results, controller design is carried out for the nonlinear mass-spring system. Discussion shows that the proposed method is less conservative than the existing references. [Copyright &y& Elsevier]

Abstract: The synchronization problem of continuous/discrete general complex dynamical networks with time-varying delays is investigated. The delays considered in this paper are assumed to vary in an interval, where the lower and upper bounds are known. Based on a piecewise analysis method, the variation interval of the time delay is firstly divided into several subintervals, by checking the variation of derivative of a Lyapunov functional in every subinterval, then the convexity of matrix function method and the free-weighting matrix method are fully used in this paper. Some new delay-dependent synchronization stability criteria are derived in the form of linear matrix inequalities. Several numerical examples show that our method can lead to much less conservative results than those in the existing references. [Copyright &y& Elsevier]

Abstract: The synchronization problem of some general complex dynamical networks with time-varying delays is investigated. Both time-varying delays in the network couplings and time-varying delays in the dynamical nodes are considered. The delays considered in this paper are assumed to vary in an interval, where the lower and upper bounds are known. Based on a piecewise analysis method, the variation interval of the time delay is firstly divided into several subintervals, by checking the variation of the derivative of a Lyapunov function in every subinterval, then the convexity of matrix function method and the free weighting matrix method are fully used in this paper. Some new delay-dependent synchronization stability criteria are derived in the form of linear matrix inequalities. Two numerical examples show that our method can lead to much less conservative results than those in the existing references. [Copyright &y& Elsevier]

Abstract: This paper is concerned with the problem of robust control for uncertain T–S fuzzy systems with interval time-varying delay, that is, the delay is assumed to be a time-varying function belonging to an interval. By defining new Lyapunov functions and making use of novel techniques to achieve delay dependence, new conditions for the existence of robust controller are obtained based on the parallel distributed compensation (PDC) method. In this article, all the conditions are shown in terms of linear matrix inequalities (LMIs), which can be solved efficiently by using the LMI optimization techniques. Two numerical examples are given to illustrate the less conservatism of the proposed method. [Copyright &y& Elsevier]

Abstract-In this paper, we are concerned with the problem of stability analysis and stabilization control design for Takagi-Sugeno (T-S) fuzzy systems with probabilistic interval delay. By employing the information of probability distribution of the time delay, the original system is transformed into a T-S fuzzy model with stochastic parameter matrices. Based on the new type of T-S fuzzy model, the delay-distribution-dependent criteria for the mean-square exponential stability of the considered systems are derived by using the Lyapunov-Krasovskii functional method, parallel distributed compensation approach, and the convexity of some matrix equations. The solvability of the derived criteria depends not only on the size of the delay but also on the probability distribution of the delay taking values in some intervals. The revisions of the main criteria in this paper can also be used to deal with the case when only the information of variation range of the delay is considered. It is shown by practical examples that our method can lead to very less conservative results than those by other existing methods. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides improved conditions for the global asymptotic stability of a class of neural networks with interval time-varying delays. A piecewise delay method is firstly proposed. In this method, the variation interval of the time delay is divided into two subintervals by introducing its central point. Then, by constructing a new Lyapunov–Krasovskii functional and checking its variation in the two subintervals, respectively, some new delay-dependent stability criteria for the addressed neural networks are derived. Numerical examples are provided to show that the achieved conditions are less conservative than some existing ones in the literature. [Copyright &y& Elsevier]

Abstract: A robust delay-distribution-dependent stochastic stability analysis is conducted for a class of discrete-time stochastic delayed neural networks (DSNNs) with parameter uncertainties. The effects of both variation range and distribution probability of the time delay are taken into account in the proposed approach. The distribution probability of time delay is translated into parameter matrices of the transferred DSNNs model, in which the parameter uncertainties are norm-bounded, the stochastic disturbances are described in term of a Brownian motion, and the time-varying delay is characterized by introducing a Bernoulli stochastic variable. Some delay-distribution-dependent criteria for the DSNNs to be robustly globally exponentially stable in the mean square sense are achieved by Lyapunov method and introducing some new analysis techniques. Two numerical examples are provided to show the effectiveness and applicability of the proposed method. [Copyright &y& Elsevier]

• The dynamic of multi-area LFC system with uncertainty and GRC under DoS attacks and time delay is described by a switched delay system. • To analyze the resilience of LFC system, we combine the piecewise Lyapunov-Krasovskii functional method and switched system method. • A criterion is derived to estimate the tolerable DoS attacks: attacks frequency, uniform bound of sleep intervals and attack intervals. Under the criterion, the design method of resilient LFC control gain is given by using LMIs techniques. Resilient load frequency control (LFC) design problem is concerned for a multi-area power system with uncertainty and physical constraint under denial-of-service (DoS) attacks and transmission delay. LFC scheme consists of a local PI control loop and additional control loop to be designed. PI control loop is subjected to constant transmission delay while additional control loop is subjected to DoS attacks. We characterize DoS attacks by attack frequency, uniform lower bound of sleep interval and uniform upper bound of attack interval. Considering DoS attacks and time delay, we describe LFC system dynamic by a switched delay system model. Further, a stability criterion is derived by using delay system method and switched system method. Under the criterion, a design method is presented to solve state feedback control gain. Finally, numerical simulations are given to verify the validness of our proposed design method. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates sampled-data robust control for T–S fuzzy systems with time delay and uncertainties. By introducing the free weighting matrices to deal with the integral items and converting the coupling time-varying matrix inequalities into a group of decoupling matrix inequalities, an innovative delay-dependent stabilization criterion is first presented. Then, a sampled-data controller is designed to stabilize the T–S fuzzy system to achieve the prescribed disturbance attenuation level, which is dependent on both the size of state delay and upper bound of allowable sampling period. Since (1) the sawtooth structure of delay is fully considered; (2) neither model transformation nor bounding techniques are employed in deriving the delay-dependent results; and (3) none of the integral items are arbitrarily ignored and magnified, the less conservative results can be expected. A practical application example is given to demonstrate the effectiveness of the proposed methods. [Copyright &y& Elsevier]