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Addressed in this paper is the reachable set estimation (RSE) problem for fuzzy‐model‐based leader‐follower multi‐agent systems with time‐varying delays and false data injection attacks. First, the aperiodic sampled‐data control is designed for the follower agents with randomly occurring false data injection attacks. Then, using the Kronecker product, the error system between the leader and the follower is obtained in a compact general form. Next, a novel Lyapunov‐Krasovskii functional is constructed with the knowledge of sampling patterns and time‐varying delays. In the framework of linear matrix inequalities, sufficient consensus conditions are determined from the H∞ $H_\\infty$performance index and Lyapunov theory to guarantee that its reachable set is enclosed by an ellipsoid in the existence of bounded perturbations. In the end, the Duffing Van der Pol oscillator and the single‐link robot arm models are employed to validate the derived theoretical results. The reachable set estimation problem is considered for the first time for leader‐follower fuzzy MASs with time‐varying delays and bounded external disturbances. The aperiodic sampled‐data control is designed for all the follower agents with the information from the leader. Moreover, the Bernoulli distribution is used for modeling the randomly occurring false data injection attacks in the controller actuator channels. The proposed theoretical findings are validated by two practical examples, that is, Duffing Van der Pol oscillator and single‐link robot arm model.

In the present study, a data-driven ripple-free design is proposed for a dual-rate sampled-data control system in which the sampling interval of the plant output is longer than the holding interval of the control input. The objective of the present study is to improve the steady-state intersample response without changing the sampled response and without using the plant model. To achieve the objective directly from controlled data, an add-on input based on the null space of steady-state step responses to an existing control system is used. The open-loop or closed-loop system to obtain the step response is assumed to be stable. In the present study, a two-degree-of-freedom design is given that redesigns the intersample output response independently of the steady-state sampled output response. In a numerical example, the proposed method is applied to a linear time-invariant single-input single-output stable system, where intersample ripples are eliminated using the add-on input that is independent of the existing sample output response in steady state.

Employing composite nonlinear feedback idea, an observer‐based digital controller is addressed for continuous‐time systems with input nonlinearity and disturbance. To achieve the regulation purpose, the equivalent discrete‐time equations are obtained via discretization. The gains of the digital integral controller are specified such that the input–output relationship becomes strictly positive real for the closed‐loop structure. Such a test condition will be verified through checking the feasibility of a linear matrix inequality. Having ensured the positive realness, the transient responses are surprisingly improved by adding suitable nonlinear feedback terms. The results are used in some constrained systems to exhibit the effectiveness of the presented mechanism over the similar one. Observer‐Based Sampled‐Data Controller in Saturated Systems via Composite Nonlinear Feedback.

This article focuses on the robust sampled‐data control for a class of uncertain switched neutral systems based on the average dwell‐time approach. In particular, the system is considered with probabilistic input delay using sampled state vectors, which are described by the stochastic variables with a Bernoulli distributed white sequence and time‐varying norm‐bounded uncertainties. By constructing a novel Lyapunov–Krasovskii functional which involves the lower and upper bounds of the delay, a new set of sufficient conditions are derived in terms of linear matrix inequalities for ensuring the robust exponential stability of the uncertain switched neutral system about its equilibrium point. Moreover, based on the stability criteria, a state feedback sampled‐data control law is designed for the considered system. Finally, a numerical example based on the water‐quality dynamic model for the Nile River is given to illustrate the effectiveness of the proposed design technique. © 2015 Wiley Periodicals, Inc. Complexity 21: 308–318, 2016

This study deals with the pinning synchronization problem for complex dynamical networks (CDNs) with Markovian jumping parameters and mixed delays under sampled‐data control technique. The mixed delays cover both discrete and distributed delays. The Markovian jumping parameters are modeled as a continuous‐time, finite‐state Markov chain. The sufficient conditions for asymptotic synchronization of considered networks are obtained by utilizing novel Lyapunov‐Krasovskii functional and multiple integral approach. The obtained criteria is formulated in terms of LMIs, which can be checked for feasibility by making use of available softwares. Lastly, numerical simulation results are presented to validate the advantage of the propound theoretical results. © 2016 Wiley Periodicals, Inc. Complexity 21: 622–632, 2016

Offshore platforms are widely used to explore, drill, produce, storage, and transport ocean resources and are usually subject to environmental loading, such as waves, winds, ice, and currents, which may lead to failure of deck facilities, fatigue failure of platforms, inefficiency of operation, and even discomfort of crews. In order to ensure reliability and safety of offshore platforms, it is of great significance to explore a proper way of suppressing vibration of offshore platforms. There are mainly three types of control schemes, i.e., passive control schemes, semi-active control schemes, and active control schemes, to deal with vibration of offshore platforms. This paper provides an overview of these schemes. Firstly, passive control schemes and several semi-active control schemes are briefly summarized. Secondly, some classical active control approaches, such as optimal control, robust control, and intelligent control, are briefly reviewed. Thirdly, recent advances of active control schemes with delayed feedback control, sliding model control, sampled-data control, and network-based control are deeply analyzed. Finally, some challenging issues are provided to guide future research directions.

This article examines the problem of estimating the states of Markovian jumping competitive neural networks, where the estimation is done using stochastic sampled-data control with time-varying delay. Instead of continuously measuring the states, the network relies on sampled measurements, and a sampled-data estimator is proposed. The estimator uses probabilistic sampling during two sampling periods, following a Bernoulli distribution. The article also takes into account the possibility of actuator failure in real systems. To ensure the exponentially mean-square stability of the delayed neural networks, the article constructs a Lyapunov-Krasovskii functional (LKF) that includes information about the bounds of the delay. The sufficient conditions for stability are derived in the form of linear matrix inequalities (LMIs) by employing modified free matrix-based integral inequalities. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.

In the framework of sampled-data control, this paper deals with the lag synchronization of chaotic neural networks with time delay meanwhile taking the impulsive control into account. By constructing a proper Lyapunov function and employing the impulsive control theory, some sufficient conditions for lag synchronization of the addressed chaotic neural networks are derived in terms of linear matrix inequalities (LMIs). The hybrid controller including sampled-data controller and impulsive controller is designed based on the established LMIs. A numerical example is provided to demonstrate the effectiveness and advantage of the obtained results.

This paper addresses the challenging problem of achieving sampled-data, velocity-free consensus for multiple Euler-Lagrange systems under irregular communication delays. While passivity-based control (PBC) is a powerful framework for such systems, existing works fundamentally require continuous feedback from neighbors, as their stability proofs cannot handle the discontinuous right-hand-side dynamics generated by sampled-data and abrupt delays. This limitation renders conventional PBC methods inapplicable in many realistic networked scenarios. This work bridges that theoretical gap by introducing a novel control and analysis method. Our strategy treats the system dynamics over continuous intervals separately from the discrete instants of discontinuity, allowing us to rigorously prove consensus. The control strategy incorporates a virtual system framework to operate without velocity measurements and successfully relaxes the impractical requirement that delays must have finite derivatives. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed consensus algorithm. Index terms: Euler-Lagrange system, Multi-agent system, Sampled-data control.