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The efficient utilization of computation and communication resources became a critical design issue in a wide range of networked systems due to the finite computation and processing capabilities of system components (e.g., sensor, controller) and shared network bandwidth. Event-triggered mechanisms (ETMs) are regarded as a major paradigm shift in resource-constrained applications compared to the classical time-triggered mechanisms, which allows a trade-off to be achieved between desired control/estimation performance and improved resource efficiency. In recent years, dynamic event-triggered mechanisms (DETMs) are emerging as a promising enabler to fulfill more resource-efficient and flexible design requirements. This paper provides a comprehensive review of the latest developments in dynamic event-triggered control and estimation for networked systems. Firstly, a unified event-triggered control and estimation framework is established, which empowers several fundamental issues associated with the construction and implementation of the desired ETM and controller/estimator to be systematically investigated. Secondly, the motivations of DETMs and their main features and benefits are outlined. Then, two typical classes of DETMs based on auxiliary dynamic variables (ADVs) and dynamic threshold parameters (DTPs) are elaborated. In addition, the main techniques of constructing ADVs and DTPs are classified, and their corresponding analysis and design methods are discussed. Furthermore, three application examples are provided to evaluate different ETMs and verify how and under what conditions DETMs are superior to their static and periodic counterparts. Finally, several challenging issues are envisioned to direct the future research.

This study presents both static and dynamic event-triggered mechanisms for the design of event-triggered stabilizing state feedback controllers for a class of uncertain nonlinear systems. Sufficient conditions based on linear matrix inequalities are first provided to guarantee the asymptotic stability of the closed-loop system. The controllers are then systematically designed. We also prove that the inter-event intervals of the considered event-triggered mechanisms are positive, therefore ensuring that the Zeno behavior does not happen. Two examples with simulations are provided to illustrate the theoretical results.

This paper investigates the adaptive event-triggered control problem for a class of nonlinear systems subject to periodic disturbances. To reduce the communication burden, a reliable relative threshold strategy is proposed. Fourier series expansion and radial basis function neural network are combined into a function approximator to model suitable time-varying disturbed function of known periods in strict-feedback systems. By combining the Lyapunov stability theory and the backstepping technique, the proposed adaptive control approach ensures that all the signals in the closed-loop system are bounded, and the tracking error can be regulated to a compact set around zero in finite time. Finally, simulation results are presented to verify the effectiveness of the theoretical results.

Management of resources is a constant topic in industrial systems. How to use minimum communication resources is of particular interest for control and estimation of networked systems. It raises the question for researchers in the field: how often should one update control and estimation? One of the most intelligent approaches is to trigger updates by events. In the literature, event-triggered control and estimation have been widely studied in the last decade. On one hand, events should be triggered sufficiently frequent to maintain system performance; on the other hand, the possibility of Zeno behavior caused by infinite frequency should be avoided. This review aims at revisiting some existing triggering techniques in a unified formulation, separated from system dynamics and control and estimation strategies. It brings readers better understanding of triggering mechanisms, the underlying technical challenges, and some promising future research topics.

This paper addresses the difficulties with connected vehicle systems (CVSs), particularly with vehicle platooning, are examined in this paper. For leader and follower-connected vehicles, the control protocol (which includes artificial delays, disturbances and proportional gains) is implemented. With tracking error systems, system dynamics are modelled while taking outside influences into consideration. Using creative thinking, a centralized event-triggered control system is implemented to maximize fleet wide communication updates. System stability is guaranteed by this centralized method in combination with quadratic form Lyapunov stability analysis. The risk of zeno behaviour is reduced by an event-triggered communication condition that is activated when a threshold is exceeded. The effectiveness of the centralized event-triggered system in improving stability and resilience in connected vehicle platooning scenarios is evaluated numerically through simulations.

This paper studies the quasisynchronization problems of reaction-diffusion neural networks (RDNNs) with time-varying delays via event-triggered control. Firstly, a static event-triggered mechanism and a dynamic event-triggered mechanism are designed to significantly reduce computation costs and save communication resources, respectively. These two different event-triggered control strategies are also able to meet the requirements of various situations. Based on the static event-triggered mechanism, the dynamic event-triggered mechanism is designed to further reduce the sampling frequency by introducing an internal dynamic variable, and several quasisynchronization criteria are derived. However, the quasisynchronization error bounds are related to triggering parameters and can be flexible adjusted, which reduces the conservatism of the existing quasisynchronization results and extends the application of proposed control strategies. Meanwhile, there exists positive lower bounds for the inter event time which can exclude the Zeno behavior. Finally, numerical simulations are given to demonstrate the superiority of the obtained theoretical results, and one example is given to show the chaotic quasisynchronization of the proposed RDNNs in the application of secure communication.

In this paper, an efficient event-triggered control is designed to address the leader-following consensus problem for the fractional-order multi-agent systems. First, in order to reduce the conservation of consensus criteria, a novel Wirtinger-based fractional-order integral inequality is proposed. Second, an adaptive control is designed by using a new event-triggered scheme without Zeno behavior, which can effectively reduce the communication cost in network. Later in order to analyze the consensus of the fraction-order leader-following systems, we employ a new approach based on fractional Lyapunov direct method. Finally, combining Wirtinger-based fractional-order integral inequality, the event-triggered adaptive control as well as the proposed consensus method, the consensus criteria of the leader-following fractional-order multi-agent systems are obtained. Two numerical examples are used to test the effectiveness and feasibility of the results presented in this study.

A discrete version of the LaSalle invariance theorem is employed to discuss event-triggered stabilization in this paper, without relying on the Lyapunov theorem. Firstly, the discrete version of the LaSalle invariance theorem is introduced as a powerful tool for analyzing event-triggered stabilization. Secondly, the globally asymptotic stabilization in probability is achieved by designing a suitable event-triggered control mechanism for discrete-time stochastic systems. Finally, the effectiveness of the controller is verified by a simulation.

This paper investigates the event-triggered control problem of networked switched systems with unstabilizable subsystems subject to mode-dependent denial-of-service (MDDoS) attacks. Unlike previous results that consider the tolerance of the entire switched systems to DoS attacks, a more general MDDoS attack is defined to limit DoS attacks of each subsystem by a mode-dependent form and mode-dependent attack duty cycle (MDADC) is proposed to exploit the tolerance of each subsystem to DoS attacks. More important, by proposed MDDoS, the tolerance of switched systems to DoS attacks is improved. First, a mode-dependent event-triggered mechanism is designed, in which the upper bound of triggered intervals of each subsystem is mode-dependent. Multiple switchings are allowed to occur within one triggered interval and the DoS attack active interval, which results in the asynchronous switchings between the controllers and the subsystems, as well as the trigger parameters and the subsystems. Secondly, MDADC is derived to ensure the global exponential stability of switched systems, which reveals the trade-off among the MDDoS attacks, unstabilizable subsystems, maximum event-triggered interval and the performance of each subsystem. Moreover, Zeno behavior is eliminated by calculating the minimum triggered interval. Finally, a numerical example and a practical example are applied to verify the effectiveness of the proposed method.

This paper designs two novel event-triggered control (ETC) schemes based on the critic learning technique for constrained discrete-time nonlinear systems. First, starting from the stability of the constrained system, a static ETC method is developed to reduce the computational burden. Then, a nonnegative dynamic variable is introduced into the static event-triggered mechanism, so as to establish the dynamic ETC method, which further improves the resource utilization rate and possesses the anti-interference ability. Moreover, a speedy value iteration architecture is designed to obtain an initially admissible optimal control policy, which can ensure the normal execution of the designed ETC methods. Finally, two experimental examples are provided to illustrate the effectiveness and superiority of the developed schemes.