Dynamic Event-triggered Scheme Research Articles

DoS attacks resilience of heterogeneous complex networks via dynamic event-triggered impulsive scheme for secure quasi-synchronization

This paper addresses the secure quasi-synchronization issue of heterogeneous complex networks (HCNs) under aperiodic denial-of-service (DoS) attacks with dynamic event-triggered impulsive scheme (ETIS). The heterogeneity of networks and the aperiodic DoS attacks, which hinder communication channels and synchronization goals, present challenges to the analysis of secure quasi-synchronization. The ETIS leverages impulsive control and dynamic event-triggered scheme (ETS) to handle the network heterogeneity and the DoS attacks. We give specific bounds on the attack duration and frequency that the network can endure, and obtain synchronization criteria that relate to event parameters, attack duration, attack frequency, and impulsive gain by the variation of parameter formula and recursive methods. Moreover, we prove that the dynamic ETS significantly reduces the controller updates, saves energy without sacrificing the system decay rate, and prevents the Zeno phenomenon. Finally, we validate our control scheme with a numerical example.

Dynamic event-triggered non-fragile filtering for singular Markovian jump systems with packet dropouts

The problem of dynamic event-based non-fragile filtering for discrete-time singular Markovian jump systems is investigated in this paper, considering network-induced delays and packet dropouts. The random packet dropout is described by a Bernoulli-distributed stochastic variable with a known distribution law. To save limited network resources, an improved dynamic event-triggered scheme is proposed. By utilizing the Lyapunov-Krasovskii stability theory, a sufficient criterion is derived to ensure the stochastic admissibility of the resulting filter error system with a desired H∞ performance index. Based on the derived criterion, a co-design algorithm for the non-fragile filter and the dynamic event-triggered scheme is proposed by solving a set of linear matrix inequalities. The effectiveness and advantages of the proposed method are illustrated by two simulation examples.

Dynamic event-triggered-based adaptive fuzzy optimized control for slowly switched nonlinear system with intermittent state constrains

This article presents a novel fuzzy event-triggered optimized strategy for slowly switched nonlinear system using reinforcement learning technique. For addressing intermittent state constraints problem, some improved shifting functions and barrier functions are designed in the adaptive backstepping process. Subsequently, by designing global performance functions with the discount term, the corresponding Hamilton-Jacobi-Bellman equation is derived and the optimal solution can be obtained under critic-actor structure. Different from the existing event-triggered methods, a novel dynamic event-triggered scheme for subsystem is developed, which not only saves communication resources, but also solves the mismatch behaviour between controller and subsystem without restriction on maximum asynchronous intervals and the number of switch within a triggering interval. Furthermore, by using modified average cycle dwell time method and Lyapunov stability theorem, all signals of system are proved to be bounded. Eventually, numerical simulation results validate the superiority of the proposed approach, and this new scheme is applied to single-link robotic manipulator.

Distributed optimization via dynamic event-triggered scheme with metric subregularity condition

In this paper, we present a continuous-time algorithm with a dynamic event-triggered communication (DETC) mechanism for solving a class of distributed convex optimization problems that satisfy a metric subregularity condition. The proposed algorithm addresses the challenge of limited bandwidth in multi-agent systems by utilizing a continuous-time optimization approach with DETC. Furthermore, we prove that the distributed event-triggered algorithm converges exponentially to the optimal set, even without strong convexity conditions. Finally, we provide a comparison example to demonstrate the efficiency of our algorithm in communication resource-saving.

Co-design of distributed dynamic event-triggered scheme and extended dissipative consensus control for singular Markov jumping multi-agent systems under periodic Denial-of-Service jamming attacks

This paper introduces a distributed dynamic event-triggered (DDET) controller meticulously crafted to achieve resilient consensus control in singular Markov jumping multi-agent systems (SMJMAs) even in the face of periodic Denial-of-Service (DoS) jamming attacks. With a dual focus on optimizing network resource utilization and fortifying against cyber threats, we propose a distributed dynamic event-triggered scheme (DDETS) grounded in the principles of sampled data consensus. In the presence of cyber attacks, we demonstrate the transformation of the original consensus control challenge within the singular multi-agent system into a robust stability control problem, centering around a singular switching error system governed by the DoS attack signal. Acknowledging the disturbances that typify real-world scenarios, this paper establishes criteria for attaining exponential stability and stochastic admissibility within the singular Markov jumping switching error system under the extended dissipative performance index. Furthermore, we present a hybrid design for the consensus controller and DDETS, delineated through a set of solvable linear matrix inequalities (LMIs). Finally, a comprehensive array of numerical examples meticulously illustrates the compelling effectiveness and unequivocal superiority of our proposed methodology.

Dynamic Event-Triggered Synchronization of Markov Jump Neural Networks via Sliding Mode Control.

This article proposes an asynchronous and dynamic event-based sliding mode control strategy to efficiently address the synchronization problem of Markov jump neural networks. By designing an adaptive law, and a triggered threshold in the form of a diagonal matrix, a special dynamic event-triggered scheme is applied to send the control signals only at triggered moments. An asynchronous sliding mode controller with gain uncertainty is designed by constructing a specified sliding manifold. Then, linear matrix inequalities are used to represent sufficient conditions for guaranteeing system synchronization. The error system trajectories are pushed onto the sliding surface by the controller. Eventually, the availability of the presented control strategy is demonstrated by an illustrative example.

Dynamic event-triggered fault detection for multi time scale systems: Application to grid connected converters

This paper deals with the fault detection problem for multi time scale systems. To save network resources, a novel dynamic event-triggered protocol with more generality and higher flexibility of parameters is proposed. The main novelties are condensed as follows, firstly, a modified fault detection observer and a quadratic residual evaluation function are synthetically designed; secondly, the sufficient condition is proved to guarantee that the estimation error system is asymptotically stable and satisfies the specified H∞ performance index; finally, a Lyapunov function is designed to composite the multi time scale perturbation parameter and the influence of the dynamic event-triggered scheme. Finally, a practical experiment on a type of grid connected converters is given to verify the proposed approach.

Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

Observer-based output feedback event-triggered bounded consensus of multi-agent systems under DoS attacks

This paper is concerned with observer-based output feedback event-triggered bounded consensus problem for linear multi-agent systems. The original multi-agent systems are transformed into the switched systems due to DoS attacks, the fast switching is applied to multi-agent systems with DoS attacks, and slow switching is applied to multi-agent systems with no DoS attacks. A novel mode-dependent dynamic event-triggered scheme and a distributed mode-dependent control protocol are proposed by using the relative output, which include some existing results as special cases. It is shown that bounded consensus can be achieved if each agent is both stabilizable and detectable, the appropriate mode-dependent average dwell time and the co-designed feedback matrices are chosen. Two algorithms are also provided to obtain the lower consensus bound. The above results are also extended to undirected topology. Finally, our theoretical results can be verified by two simulation examples.

Fully distributed consensus of linear multi-agent systems via dynamic event-triggered control

This paper investigates the fully distributed consensus control problem for general linear multi-agent systems via dynamic event-triggered scheme. To address the need to reduce network communication burdens and avoid involving any global features of multi-agent networks, a novel fully distributed controller based on the open-loop state estimator of agents is presented. To improve anti-interference ability and practicability of the proposed approach, an event-triggered strategy which can guarantee a precise lower bound of triggering intervals for each follower is designed with a virtual internal variable. Then, the stability of the multi-agent systems is analyzed without any global network information. Several simulation experiments are conducted to illustrate theoretical results.

Observer-based dynamic event-triggered adaptive control for uncertain nonlinear strict-feedback systems

This paper proposes an observer-based dynamic event-triggered adaptive control approach for uncertain nonlinear strict-feedback systems. Initially, an observer for unmeasurable states is constructed. Subsequently, employing backstepping technique, the output-feedback adaptive control law and parameter adaptive law are developed. The tuning function method is used to avoid the over-parameterization problem in parameter adaptive law design. To lower the data exchange rate within the network, a dynamic event-triggered scheme is formulated to allow real-time update control signal. Through Lyapunov theory analysis, the resulting closed-loop system is demonstrated to be stabilized, and the occurrence of Zeno behavior is effectively prevented. Finally, the simulation example validates the obtained result of the presented design approach.

Dynamic event-triggered fuzzy control for nonlinear singular semi-Markovian jump systems via state decomposition approach

This paper addresses the dynamic event-triggered fuzzy control problem of nonlinear singular semi-Markovian jump systems. Firstly, the interval type-2 fuzzy model is utilized to approximate nonlinear singular semi-Markovian jump systems. Secondly, by employing the state decomposition approach, the interval type-2 fuzzy singular system is decomposed into a differential equation and an algebraic equation. Thirdly, a new periodic dynamic event-triggered scheme with the adaptive variable is proposed to further relieve the communication pressure while ensuring the system performance. The hidden semi-Markov model is used to describe the phenomenon that the modes of fuzzy controller and the modes of original system are asynchronously operational. By designing the asynchronous event-triggered fuzzy controller based on quantized decomposed state vectors and constructing suitable Lyapunov-Krasovskii functional, sufficient conditions are derived to guarantee that the closed-loop fuzzy singular system is stochastically admissible. Finally, two simulation examples are provided to verify the validity and advantages of obtained results.

Exponential Stabilization of Delayed Switched Systems: A Discrete Dynamic Event-Triggered Scheme

Exponential Stabilization of Delayed Switched Systems: A Discrete Dynamic Event-Triggered Scheme

Improved dynamic event-triggered [formula omitted] control for networked fuzzy singularly perturbed systems with hidden Markov fading channels

In this paper, the dynamic event-triggered H∞ control problem is explored for networked fuzzy slow sampling singularly perturbed systems (S3PSs) subject to hidden Markov fading channels. To alleviate the communication burden more effectively, an improved dynamic event-triggered scheme (DETS) is constructed for networked fuzzy S3PSs, under which two auxiliary internal dynamic variables are considered into event-triggered condition. The fading channel phenomena with randomly time-varying amplitudes are characterized by the finite state Markov process. Meanwhile, considering the actual network mode may be unmeasurable, a hidden Markov mode detector is exploited to estimate the actual network mode, by which the control signal can be adjusted appropriately. By constructing the singular perturbation parameter (SPP)-dependent Lyapunov functional, sufficient conditions are obtained to guarantee the mean square stability of networked fuzzy S3PSs. Besides, the numerical ill-conditioned problem of networked fuzzy S3PSs can be avoided. Finally, a tunnel diode circuit example is proposed to illustrate the effectiveness of the main results.

Fully Distributed Dynamic Event-Triggered Bipartite Formation Tracking for Multiagent Systems With Multiple Nonautonomous Leaders.

Considering that cooperative interactions and antagonistic interactions between neighboring agents may exist simultaneously in practice, this article studies the bipartite time-varying output formation tracking (BTVOFT) problems for homogeneous/heterogeneous multiagent systems with multiple nonautonomous leaders under switching communication networks. First, a full-dimensional observer-based nonsmooth distributed dynamic event-triggered (DDET) output feedback control scheme is proposed to ensure that BTVOFT is achieved, and the Zeno behavior is excluded. Note that the nonsmooth distributed control scheme requires global communication network information and may cause unexpected chattering effect, and the design cost of full-dimensional observer is relatively high. Thus, a reduced-dimensional observer-based continuous fully DDET scheme is proposed. Compared with the existing event-triggered schemes, the dynamic event-triggered scheme can ensure larger interevent times by introducing an additional internal dynamic variable. Finally, the effectiveness and performance of the theoretical results are validated by numerical simulations.

Hybrid Nash Equilibrium Seeking Under Partial-Decision Information: An Adaptive Dynamic Event-Triggered Approach

This paper is concerned with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hybrid</i> Nash equilibrium (NE) seeking problem over a network in a partial-decision information scenario. Each agent has access to both its own cost function and local decision information of its neighbors. First, an adaptive gradient-based algorithm is constructed in a fully distributed manner with the guaranteed convergence to the NE, where the network communication is required. Second, in order to save communication cost, a novel event-triggered scheme, namely, edge-based adaptive dynamic event-triggered (E-ADET) scheme, is proposed with on-line-tuned triggering parameter and threshold, and such a scheme is proven to be fully distributed and free of Zeno behavior. Then, a hybrid NE seeking algorithm, which is also fully distributed, is constructed under the E-ADET scheme. By means of the Lipschitz continuity and the strong monotonicity of the pseudo-gradient mapping, we show the convergence of the proposed algorithms to the NE. Compared with the existing distributed algorithms, our algorithms remove the requirement on global information, thereby exhibiting the merits of both flexibility and scalability. Finally, two examples are provided to validate the proposed NE seeking methods.

Global output feedback control for uncertain strict-feedback nonlinear systems: A logic-based switching event-triggered approach

This paper addresses the global output-feedback stabilization for a class of uncertain nonlinear systems via a switching event-triggered approach. Typically, the system growth rates are allowed to be arbitrary unknown non-polynomial functions of system output. Note that such nonlinearities cannot be handled by generalizing the design rationales employed in polynomial rate cases. For this reason, an event-triggered mechanism together with a logic-based switching mechanism is proposed to determine not only when to sample but also when to switch the control parameter. With the help of the switching control parameter, an observer-based control scheme is developed to achieve global output-feedback stabilization. Particularly, the control parameter can be adaptively adjusted to a sufficiently large value, so the proposed control scheme has a stronger capability to deal with large uncertainties, inherent nonlinearities, and sampling errors of the system. For more efficient resource saving, an extended investigation is presented by constructing a dynamic event-triggered scheme. Finally, two simulation examples are given to illustrate the effectiveness of the switching event-triggered schemes.

Dynamic Event-triggered Control for Nonlinear PDE System with Actuator Dead-zone

A dynamic event-triggered network control scheme is proposed for a class of distributed parameter systems with time delay and nonlinearity. The security control of the PDE system under DOS attack based on dynamic event-triggered is studied. A dynamic event-triggered scheme is adopted to reduce the communication burden, that is, the sampling data will be sent only when the original trigger condition is violated. At the same time, a new model including denial of service attack (DOS) is established to describe the random network attack. When a hacker launches a DoS attack, it prevents the sampling data from reaching the destination by interfering with the network channel. DOS attacks follow no specific pattern and exhibit non-periodic behavior or irregular probability distribution. A mathematical model of a state-dependent uncertain system with an event-triggered scheme was established to study denial of service attacks. By using the Lyapunov-Krasocskii stability theory and linear matrix inequality tools, sufficient conditions were derived to ensure the index mean square stability of the state-dependent uncertain system. Based on this, sufficient conditions for the asymptotic stability of the closed-loop network control system and the expected performance index of the system were obtained. Numerical examples verified the feasibility of the method, and controller design validated the applicability of the theoretical results.

Dynamic event-based forecasting-aided state estimation for active distribution systems subject to limited communication resource

In this paper, the dynamic event-based forecasting-aided state estimation (FASE) method is developed to deal with the state estimation problem of the active distribution system (ADS) subject to communication constraints and non-linear measurements. The proposed method first constructs a state-space model of the ADS to describe system state time evolution. Secondly, to use communication resources more effectively, the dynamic event-triggered scheme (ETS) is exploited to schedule the data transmission. Aiming at the problem of the ADS in the presence of the non-linear measurement, the Gaussian integral is approximated by the spherical cubature rule to obtain the mean and covariance of the state variables after non-linear transformation. Moreover, the upper bound of the estimation error covariance containing non-triggering errors is derived, and then minimized by suitably designing filter gain, thus developing the dynamic event-triggered cubature Kalman filter (DET-CKF) algorithm to perform state estimation for ADSs. Finally, a series of simulation experiments are conducted to verify the effectiveness of the developed FASE method.

Cooperative Fault-Tolerant Output Regulation of Linear Heterogeneous Multiagent Systems via an Adaptive Dynamic Event-Triggered Mechanism.

This article considers the problem of cooperative fault-tolerant output regulation of linear heterogeneous multiagent systems with actuator faults where the exosystem matrix is known by part of the followers. An adaptive dynamic event-triggered scheme is proposed to avoid continuous communication between followers, removing the assumption that global information should be known for controller design. Different from the existing open-loop estimation method for obtaining intermittent communication, the approach proposed in this article does not require that the system matrices of all agents be the same and known a prior. Compared with the existing static or periodic event-triggered mechanism (ETM), by introducing dynamic variables, a more general form than an exponential function, the proposed adaptive dynamic event-triggered condition provides the potential to save energy and obtain better performance. It is demonstrated that the suggested event-triggered control (ETC) method performs cooperative fault-tolerant output regulation for all followers in a completely distributed way with intermittent communication while excluding Zeno behavior. Finally, a simulation example is carried out to illustrate the efficacy of the suggested strategy.