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Cyber Physical Systems (CPSs) are defined as the integrations of computation, control, and communication to obtain a prespecified behaviour of the physical processes. Due to their nature, CPSs could be highly affected by security threats. In this research, a secure filter for discrete-time delayed nonlinear systems affected by the two major kinds of cyber attacks i.e. denial-of-service (DoS) and deception attacks is proposed. The cyber attacks are modelled as Bernoulli distributed white sequences with variable probabilities. First, a predefined level of security is guaranteed by setting a sufficient condition using the techniques of stochastic analysis. Second, we obtain the gains of the proposed filter by solving a linear matrix inequality using YALMIP and MATLAB/Simulink. Finally, a numerical example is solved to show the effectiveness of this method on CPSs. [ABSTRACT FROM AUTHOR]

This article studies the consensus problem for discrete‐time nonlinear multiagent systems with time delay. Based on an asynchronous event‐triggered mechanism where local information of a communication graph is involved, a distributed consensus protocol is proposed to reduce the network communication congestion for achieving state consensus for multiagent systems with nonlinear perturbations. To avoid complications involving data fusion, this distributed consensus protocol allows every agent to broadcast its state at its own triggering condition instead of using continuous updates and without continuous monitoring of the triggering condition. To save the energy consumption involved in a consensus protocol, the proposed event‐triggering guaranteed cost is investigated in this article for multiagent systems. We select an agent as a leader that is constrained by its neighbors and controlled by the proposed protocol as other agents. It has been theoretically demonstrated that the consensus problem of multiagent systems with nonlinear perturbation and time delays can be achieved if the control gains and the triggering parameters are appropriately selected. Sufficient conditions are given to guarantee that the agents achieve consensus. Moreover, the gain matrix and triggering parameters of the proposed protocol are cast into matrix inequalities conditions. A simulation example is given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate the problem of global exponential stability analysis for a class of bidirectional associative memory (BAM) neural networks with interval time-delays. Improved exponential stability condition is derived by employing new Lyapunov–Krasovskii functional and the integral inequality. Several special cases of interest are derived. The developed stability criteria are delay dependent and characterized by linear matrix inequalities (LMIs). The developed results are shown to be less conservative than previous published ones in the literature. Finally, simulations of two numerical examples are provided to demonstrate the efficacy of our approach. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate the problem of robust global exponential stability analysis for a class of neutral-type neural networks. The interval time-varying delays allow for both slow and fast time-varying delays. The values of the time-varying uncertain parameters are assumed to be bounded within given compact sets. Improved global exponential stability condition is derived by employing new Lyapunov–Krasovskii functional and the integral inequality. The developed nominal and robust stability criteria is delay-dependent and characterized by linear-matrix inequalities (LMIs). The developed results are less conservative than previous published ones in the literature, which are illustrated by representative numerical examples. [Copyright &y& Elsevier]

In this paper, we provide a novel solution to the problem of persistent bounded disturbance rejection in linear discrete-time systems with time-varying delays. The solution is developed based on the tools of invariant set analysis and Lyapunov–Krasovskii functional method. As an integral part of the solution, we derive less conservative sufficient conditions on robust attractor for discrete-time systems with delays in terms of strict linear matrix inequalities (LMIs) to guarantee that the desired ℓ1-performance is achieved. A robust dynamic output-feedback controller with arbitrary order is designed and the associated gain is determined using strict LMIs. The developed results are tested on a representative example. [ABSTRACT FROM PUBLISHER]

Abstract: This paper establishes new robust delay-dependent stability and stabilization methods for a class of nonlinear discrete-time systems with time-varying delays. The parameter uncertainties are convex-bounded and the unknown nonlinearities are time-varying perturbations satisfying Lipschitz conditions in the state and delayed-state. An appropriate Lyapunov functional is constructed to exhibit the delay-dependent dynamics and compensate for the enlarged time-span. The developed methods for stability and stabilization eliminate the need for over bounding and utilize smaller number of LMI decision variables. New and less conservative solutions to the stability and stabilization problems of nonlinear discrete-time system are provided in terms of feasibility-testing of new parametrized linear matrix inequalities (LMIs). Robust feedback stabilization methods are provided based on state-measurements and by using observer-based output feedback so as to guarantee that the corresponding closed-loop system enjoys the delay-dependent robust stability with an gain smaller that a prescribed constant level. All the developed results are expressed in terms of convex optimization over LMIs and tested on representative examples. [Copyright &y& Elsevier]

Abstract: This paper investigates the problem of robust global exponential stability analysis for uncertain neural networks with interval time-varying delays. The time-delay pattern is quite general and including fast time-varying delays. The values of the time-varying uncertain parameters are assumed to be bounded within given compact sets. The activation functions are monotone nondecreasing with known lower and upper bounds. Novel stability criteria are developed by employing new Lyapunov–Krasovskii functional and the integral inequality. The developed stability criteria are delay dependent and characterized by linear matrix inequalities (LMIs)-based conditions. The developed stability results are less conservative than previous published ones in the literature, which is illustrated by a representative numerical example. [Copyright &y& Elsevier]

Abstract: The problem of designing a globally exponentially convergent state estimator for a class of delayed neural networks is investigated in this paper. The time-delay pattern is quite general and including fast time-varying delays. The activation functions are monotone nondecreasing with known lower and upper bounds. A linear estimator of Luenberger-type is developed and by properly constructing a new Lyapunov–Krasovskii functional coupled with the integral inequality, the global exponential stability conditions of the error system are derived. The unknown gain matrix is determined by solving a delay-dependent linear matrix inequality. The developed results are shown to be less conservative than previously published ones in the literature, which is illustrated by a representative numerical example. [Copyright &y& Elsevier]

Abstract: The generalized control problem for a class of linear discrete-time switched systems with constant unknown delays is investigated. New linear matrix inequalities (LMIs) characterization based on switched Lyapunov–Krasovskii functional are established to guarantee the asymptotic stability and generalized performance. Design of generalized state feedback and dynamic output-feedback controllers are developed. A numerical example is worked out in detail to illustrate the theoretical developments. [Copyright &y& Elsevier]

In this paper, new results are established for the delay-dependent problems of dissipative analysis and state-feedback synthesis of singular time-delay (STD) systems with polytopic uncertainties. The developed results for the nominal singular system encompass available results on ℋ∞ approach, passivity and positive realness for STD systems as special cases. All the sufficient stability conditions are cast as linear matrix inequality-based feasibility tests. Robust dissipativity results are also derived. Numerical examples are provided. [ABSTRACT FROM PUBLISHER]

Abstract: A class of non-linear discrete-time systems with state-delay is considered. We develop an LMI-based analysis and design procedures to check primarily into the robust stability of discrete-time systems with state-delay and bounded non-linearities. Then we address the robust stabilization using nominal and resilient feedback designs. In both cases the trade-off between the size of the controller gains and the bounding factors is illuminated and incorporated into the design formalism. Seeking computational convenience, all the developed results are cast in the format of linear matrix inequalities (LMIs) and several numerical examples are presented throughout the paper to illustrate the feasibility of the theoretical developments. [Copyright &y& Elsevier]

This paper develops new results to the problem of simultaneous feedback stabilization using static output feedback (SOF) control for a finite collection of linear dynamical systems with unknown state delay. We establish tractable synthesis conditions for nominal SOF controllers and subsequently extend the results to resilient SOF to cope with possible additive controller gain perturbations. In both cases, the design of SOF controllers is based on guaranteed cost and ℋ∞ approaches. Previous related results are recovered and all the developed results are conveniently cast in the format of linear matrix inequalities. A numerical example is presented. [ABSTRACT FROM PUBLISHER]

In this paper, the problems of passivity and passification of a class of linear jumping time-delay systems are investigated. The jumping parameters are modelled as a continuous-time, discrete-state Markov process. The interplay between time-delay pattern and passivity concept is examined leading to three distinct cases: passivity with weak delay dependence, passivity with strong delay dependence (PSDD) and passivity with functional time delay. In the case of PSDD, a new state transformation is developed to exhibit the delay dependence. It is established that the passivity conditions can always be cast in a linear matrix inequality format. Complete results on state feedback passification are subsequently developed. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problems of robust performance analysis and control synthesis for a class of linear, Markovian jump continuous-time systems with parameter uncertainty and unknown state-delay. The parameter uncertainty is real time-varying norm-bounded and the state-delay is a constant within a prescribed interval. For the robust performance analysis problem, we develop appropriate notions of robust stochastic stability with weak and strong delay dependence. In both cases, we establish that the adopted notion guarantees an upper bound on a linear quadratic cost function. For the synthesis problem, we prove that a robust state-feedback controller can always be constructed to render the closed-loop Markovian jump system robustly stochastically stable while guaranteeing a prescribed level of performance. The developed results are expressed in terms of algebraic Riccati or linear matrix inequalities. Two numerical examples are presented. [ABSTRACT FROM AUTHOR]

A new state transformation exhibiting the delay-dependent behaviour for a class of uncertain delayed systems with Markovian jump parameters is developed to solve the problem of H∞ control. The jumping parameters are modelled as a continuous-time, discrete-state Markov process and the parametric uncertainties are assumed to be real, time-varying and norm-bounded that appear in the state, input and delayed-state matrices. The input and state delays are known. Complete results for instantaneous state feedback control designs are established which guarantee the strong-delay dependent stochastic stability with a prescribed H∞-performance. The solutions are provided in terms of a finite set of coupled linear matrix inequalities. A numerical example is given to show the potential of the proposed techniques. [ABSTRACT FROM PUBLISHER]

This paper deals with the problems of decentralized robust stabilization and robust H∞ performance for a class of continuous‐time, interconnected jumping time delay systems with norm‐bounded parametric uncertainties. The delays are unknown time varying in the state of each subsystem as well as in the interconnections between the subsystems. A class of decentralized observer‐based feedback controllers is developed to render the closed‐loop interconnected system asymptotically stable. All the design effort is undertaken at the subsystem level. It is shown that the robust control design problem can be essentially solved in term of a family of linear matrix inequalities. It has been established that the developed results encompass several existing results as special cases. The developed theory is illustrated by simulation of a multi‐reach pollution model of a representative segment of the River Nile. [ABSTRACT FROM PUBLISHER]

The problems of stochastic stabilization and control for a class of linear time‐delay systems with Markovian jump parameters via output feedback are investigated. The jumping parameters are modelled as a continuous‐time, discrete‐state Markov process. The delay factor is unknown and time‐varying with a known bound. Concepts of weak and strong delay‐dependent stochastic stability are introduced and appropriate criteria to be applied to the jumping systems are developed. The control objective is to design an output–feedback controller such that stochastic stability and a prescribed H∞‐like performance for a closed‐loop system are guaranteed. We establish that the stability and stabilization problems for the time‐delay Markovian jump systems can be essentially solved in terms of the solutions of a finite set of coupled linear matrix inequalities. We show that in the case of weak delay‐dependency, the controller is of arbitrary order and the associated gain matrices are computed implicitly. In the case of strong weak coupling the controller is of full order and explicit expressions are given for the associated gain matrices. [ABSTRACT FROM PUBLISHER]

Presents a study that examined the control problem of a class of uncertain nonlinear time-delay systems. Problem statement and preliminaries; Information on robust state-feedback control; Details about a robust observer-based controller.