In this paper, the stability analysis and H∞controller design problem are investigated for a class of randomly sampled-data systems with uniformly bounded sampling errors and random denial-of-service (DoS) attacks, with an application to a fourth-order interleaved flyback module-integrated converter (IFMIC). First, a discrete-time stochastic model is formulated for the considered system affected by random sampling errors and DoS attacks. A stability condition that incorporates the expectation of a stochastic, nonlinear, and attack-dependent coupling matrix is then derived through a (reduced-order) Vandermonde matrix method. Subsequently, the existence of this expectation is established, followed by the application of the Kronecker product operation to effectively decompose the resulting matrix expectation. On this basis, an H∞synthesis algorithm is designed to guarantee the exponential mean-square stability and H∞performance of the discrete-time system. Furthermore, a special case considering only random sampling errors is analyzed, along with its corresponding H∞controller. Compared with existing studies, the proposed method yields a fixed-dimensional linear matrix inequality (LMI) condition that remains unaffected by the upper bound of consecutive DoS attacks and does not require reformulation when network conditions vary, thus enhancing both computational efficiency and implementation flexibility. Finally, the effectiveness of the proposed algorithm is demonstrated through simulation studies on a fourth-order IFMIC under different operations.

Toward exploring the positive impact of media debunking and random blocking on the spread of rumors, we discuss a stochastic hybrid control strategy that combines an individual and media debunking method, a continuous stochastic blocking method, and an impulse interruption method. Using stochastic analysis, the almost sure exponential stability of the controlled system is analyzed, along with the expression of control intensities. To balance rumor suppression, minimize control costs, and enhance the generality of control, a data-driven machine learning (ML) approach is developed to provide suboptimal control solutions. Numerical simulations based on two real-case datasets are carried out to validate the theoretical results and evaluate the potential impact of the model-based, data-driven stochastic hybrid control strategy.

In this article, the stability analysis and synthesis issues of networked control systems with asynchronous sensors and controllers are studied, where the stochastic variable obeying a certain probability distribution is introduced to characterize the clock offset between the sensor and the controller. First, a continuous-time framework covering random clock offsets and consecutively lost packets is established. An appropriate discrete-time stochastic augmented model is then constructed to investigate the analysis and synthesis problems of resulting continuous-time framework. Therefore, we prove that the stochastic stability of the discrete-time model implies the stochastic stability of resulting continuous-time system. Based on the discrete-time stochastic augmented model, the random and highly nonlinear terms are decoupled with the help of the law of total expectation, Kronecker product operation, and reduced-order confluent Vandermonde matrix. Subsequently, we present the stability condition in the form of linear matrix inequality and design the desired gain matrix such that the original continuous-time system is stochastically stable. Finally, two numerical examples and a practical example are utilized to clarify the practicability of the designed strategy.

In this article, the stochastic analysis and$H_{\infty }$controller design problems of networked systems with packet dropouts and false data injection attacks are investigated. Different from the existing literature, we focus on the linear networked systems with external disturbances and both sensor–controller channel and controller–actuator channel are studied. First, we present a discrete-time modeling framework that leads to a stochastic closed-loop system with randomly varying parameters. To facilitate the analysis and$H_{\infty }$control of resulting discrete-time stochastic closed-loop system, an equivalent yet analyzable stochastic augmented model is further constructed by matrix exponential computation. Based on this model, a stability condition is derived in the form of linear matrix inequality (LMI) with the aid of a reduced-order confluent Vandermonde matrix, Kronecker product operation, and law of total expectation. Specifically, the dimension of the LMI obtained in this article does not increase as the upper bound of consecutive packet dropouts does, which is also different from the existing literature. Subsequently, a desired$H_{\infty }$controller is obtained such that the original discrete-time stochastic closed-loop system is exponentially mean-square stable with a prescribed$H_{\infty }$performance. Finally, a numerical example and a direct current motor system are exploited to substantiate the effectiveness and practicability of the designed strategy.

This study is concerned with the$H_{\infty }$control issue of networked systems with consecutively lost packets using sampled-data. First, we establish a discrete stochastic system for the networked system with external disturbances and consecutively lost packets. To enable$H_{\infty }$performance analysis, an equivalent but analyzable stochastic framework is then derived by using matrix exponential computation. Subsequently, by law of total expectation, Kronecker product operation, and eigenvalue decomposition approach, we compute the expectation of a coupling term with significant nonlinearity and randomness. Based on this, a stabilization controller is constructed that ensures the resulting discrete stochastic system’s exponential mean-square stability with a prescribed$H_{\infty }$performance. Unlike the existing literature, the linear matrix inequalitys (LMIs) dimension derived in this article does not change along with the maximum number of consecutively lost packets, which prevents an LMI with high-computing complexity. Finally, the validity and applicability of the algorithm are demonstrated by a numerical example and an example using a satellite system.

This article addresses the issue of output-feedback consensus control of multiagent systems under the directed topology and subject to bounded external disturbances. By employing a smooth time-varying function, a distributed practical predefined-time (PPT) observer is developed to estimate the reference trajectory for the entire team (i.e., the leader's state) and a practical preset-time extended-state observer is also proposed to estimate bounded disturbances and unmeasurable system states. Next, a novel continuous and nonsingular PPT consensus control law is designed on the basis of the observers. Furthermore, the designed control protocol can achieve PPT stability, that is, consensus tracking errors are enforced to a neighborhood around zero within a predetermined time, which can be specified a priori, independent of initial states of agents and/or any other design parameters. Finally, illustrative numerical examples, including a comparative one, are provided to demonstrate the performance of the present predefined-time control approach.

This article focuses on the sampled-data synchronization issue for a class of complex dynamical networks (CDNs) subject to noisy sampling intervals and successive packet losses. The sampling intervals are subject to noisy perturbations, and categorical distribution is used to characterize the sampling errors of noisy sampling intervals. By means of the input delay approach, the CDN under consideration is first converted into a delay system with delayed input subject to dual randomness and probability distribution characteristic. To verify the probability distribution characteristic of the delayed input, a novel characterization method is proposed, which is not the same as that of some existing literature. Based on this, a unified framework is then established. By recurring to the techniques of stochastic analysis, a probability-distribution-dependent controller is designed to guarantee the mean-square exponential synchronization of the error dynamical network. Subsequently, a special model is considered where only the lower and upper bounds of delayed input are utilized. Finally, to verify the analysis results and testify the effectiveness and superiority of the designed synchronization algorithm, a numerical example and an example using Chua's circuit are given.

This paper studies the modeling and synchronization problems for stochastic complex dynamical networks subject to consecutive packet dropouts. Different from some existing research results, both probability characteristic and upper bound of consecutive packet dropouts are involved in the proposed approach of controller design. First, an error dynamical network with stochastic and bounded delay is established by step-delay method, where the randomness of the bounded delay can be verified later by the probability theory method. A new modeling method is introduced to reflect the probability characteristic of consecutive packet dropouts. Based on the proposed model, some sufficient conditions are proposed under which the error dynamical network is globally exponentially synchronized in the mean square sense. Subsequently, a probability-distribution-dependent controller design procedure is then proposed. Finally, two numerical examples with simulations are provided to validate the analytical results and demonstrate the less conservatism of the proposed model method.

In this paper, we discuss the modeling and stabilization problems for a class of discrete-time stochastic networked systems (DSNSs) subject to successive packet losses. The system under consideration is transformed into a stochastic one with bounded stochastic delay. Considering that the stochastic delay is characterized by nonuniform distribution, a new equivalent model is then constructed that enables the DSNS's controller design to benefit from knowing the probability characteristic of packet losses. Specially, to verify this feature, the probabilities of the delay can be explicitly obtained by utilizing the formula of total probability, which is critical to model transformation and analyze practical problems that exist in DSNSs. Based on the proposed model, sufficient conditions are established under which the globally mean-square asymptotic stability of resulting stochastic delay closed-loop system is guaranteed, and a delay-distribution-dependent design procedure is then proposed. A numerical example with simulation is provided to validate the analytical results and demonstrate the effectiveness of the design procedure.

Event-triggered schemes are characterized in less communication traffic while maintaining the resulting controlled plant's desired stability and performance criteria. In the presence of packet dropouts, this paper is concerned with the modeling and control problems for a class of discrete-time stochastic systems with event-triggered schemes. Two different mathematical analysis methods are proposed to model the packet loss when an event-triggered scheme is subject to packet loss. First, a stochastic distributed sequence satisfying the Bernoulli process is utilized to model the triggered packets transmitted in the communication networks. Considering the difference between time-triggered and event-triggered schemes, an equivalent model with a random sequence not satisfying a Bernoulli distribution process is also analyzed, which is not the same as some existing results in the literature. Then, the mean-square exponential stability of resulting augmented system is guaranteed and the prescribed H∞performance level is achieved by solving resulting discrete P-problem. Two examples with simulations are provided to validate the analytical results and demonstrate the effectiveness of the proposed co-design techniques.

This paper considers the sample-data-based consensus problem of multiagent systems with time-varying delay and packet losses. To distinguish the time delays caused by network-induced time-delay and packet losses, the switched system is utilized. A lower gain controller is designed based on the solution of a parametric algebraic Riccati equation. The Lyapunov stability theory is utilized to obtain the limitations on the frequency and the duration of packet losses which guarantees the consensus of multiagent systems. On the other hand, we theoretically prove that refined time-delay function can reduce the conservatism. A simulation example is given to illustrate the effectiveness of the proposed method.