Event-triggered Impulsive Control Research Articles

Input-to-state stability of impulsive switched systems under mode-dependent event-triggered impulsive control

This paper aims to investigate input-to-state stability (ISS) of nonlinear impulsive switched systems under mode-dependent event-triggered impulsive control (MDETIC) method. A novel mode-dependent event-triggered mechanism (MDETM) is devised, where triggering impulsive instants are determined by some predesigned event conditions. Different from existing MDETM, there are two types of impulsive behavior involved, including the impulsive behavior of system itself and event-triggered one. The novel MDETM not only reduces communication cost and energy consumption but also excludes “Zeno behavior.” Then, the ISS criteria of the closed-loop system are established based on MDETIC strategy, admissible edge-dependent average dwell time (AED-ADT), and admissible edge-dependent average impulsive interval (AED-AII) methods. Finally, two examples are given to verify the effectiveness of the main results.

Synchronization of fractional-order quaternion-valued neural networks with image encryption via event-triggered impulsive control

The finite-time synchronization and impulsive synchronization of fractional-order quaternion-valued neural networks (FOQVNNs) with delay are investigated in this research. To begin, instead of employing a decomposition method, a Lyapunov direct approach is proposed to achieve the finite-time synchronization of FOQVNNs using event-triggered control based on state errors. The settling time is then estimated using a unique fractional differential inequality. The event-triggered impulsive controller, which updates only during impulsive instants, is proposed to be more inexpensive and efficient. Then, utilizing fractional Lyapunov theory and the comparison principle, several novel quaternion-valued linear matrix inequalities criteria are defined to assure the impulsive synchronization of the delayed FOQVNNs. Furthermore, the positive lower bound of the inter-event time is obtained to exclude the Zeno behavior. As proof of the feasibility and validity of these theoretical findings obtained, numerical examples are provided. At last, the use of the event-triggered control technique for FOQVNNs in image encryption and decryption is demonstrated and validated.

Stability of impulsive and switched stochastic delay systems via the event-triggered impulsive mechanism

Under the event-triggered impulsive mechanism, this work introduces the pth moment (integral) input-to-state stability (p-(i)ISS) for a general group of impulsive and switched stochastic delay systems. Using the means of mode-dependent average dwell time and mode-dependent average impulsive interval, some sufficient conditions of p-ISS and p-iISS are supplied. By incorporating the input of subsystems and impulses into the triggering functions, two distinct types of event-triggered impulsive constraint is proposed, which is defined as mode-dependent event-triggered impulsive mechanism with input (MDETIMI). Different from the traditional event-triggered impulsive control, two MDETIMI strategy are individually discussed, which one is the supremum of K∞ function of subsystem input and the superposition of impulsive input, and the other is the integral of K∞ function of subsystem input and the superposition of impulsive input. Moreover, it is unveiled that even with the indeterminate derivatives of the Lyapunov functions, the Zeno phenomenon can effectively be avoided by using MDETIMI strategy. Finally, an example shows the effectiveness and practicability of the results.

Privacy-preserving bipartite output consensus for continuous-time heterogeneous multi-agent systems via event-triggered impulsive control

Privacy-preserving bipartite output consensus for continuous-time heterogeneous multi-agent systems via event-triggered impulsive control

Mean-square bounded synchronization of fractional-order chaotic Lur’e systems under deception attack

This paper discussed the mean-square bounded synchronization (MSBS) of fractional-order chaotic Lur’e systems (FOCLSs) in the presence of deception attacks. Firstly, it was assumed that the channel of the controller to the actuator was subjected to stochastic deception attacks, which were modeled by the Bernoulli stochastic variable. Secondly, impulsive control was proposed to achieve the aim of the MSBS of FOCLSs. Moreover, the event-triggered mechanism (ETM) is added to the impulsive control to decrease the controller update times and save computing resources consumption. Applied the fractional-order calculus, the Laplace transform, and the definition of MSBS, sufficient criteria were derived to guarantee the MSBS of FOCLSs, with the criteria being dependent on the order of the system. The upper bound of the synchronization error is given for the error system under impulsive control and event-triggered impulsive control (ETIC), respectively. Finally, Chua’s circuit was employed to indicate the practicability of the MSBS of FOCLSs.

More Practical Coupled Neural Network Systems Under Event-Triggered Impulsive Control: A Novel Study Approach

More Practical Coupled Neural Network Systems Under Event-Triggered Impulsive Control: A Novel Study Approach

Event-Triggered Impulsive Control for Input-to-State Stabilization of Nonlinear Time-Delay Systems.

This article investigates the event-triggered impulsive control (ETIC) problem for a class of nonlinear time-delay systems subject to exogenous disturbances. An original event-triggered mechanism (ETM) which utilizes the information of system state and external input is constructed based on Lyapunov function approach. To achieve the input-to-state stability (ISS) of the considered system, some sufficient conditions are presented, in which the underlying relationship among ETM, exogenous input, and impulse action is established. Furthermore, the possible Zeno behavior induced by the proposed ETM is excluded simultaneously. As an application, the design criterion of ETM and impulse gain is put forward for a class of impulsive control systems with delay according to the feasibility of some linear matrix inequalities (LMIs). Finally, two examples with numerical simulations are provided to confirm the effectiveness of the developed theoretical results, where the synchronization issue of delayed Chua's circuit is considered.

A rumor propagation model in multilingual environment with time and state dependent impulsive control

In this paper we are interested in the problem of modeling, analysis and control of rumor spreading on online social networks. As the diversity of languages and the difference of user nodes in the network, a heterogeneous rumor spreading model with two language spreaders is proposed, and the impulsive isolation control strategy is considered. Firstly, the model with periodic impulsive isolation control and time-delay recovery rate is discussed. Based on the stability theory of impulsive differential equations, some conditions regarding the impulsive period and control gains are given for the rumor asymptotically disappearance and persistent existence. Secondly, a new type of event-triggered impulsive isolation control method is developed to address the tradeoff between restraining rumor and minimizing the cost of control, and some conditions are given to make the rumor disappear asymptotically. Furthermore, an improved event-triggered mechanism is established based on the fixed-time stability theory, which provides the conditions for the rumor to disappear within a fixed-time. Finally, some numerical simulations and an actual example are given to verify the rationality of the model and the effectiveness of the control methods.

Security synchronization problem for stochastic complex networks via event-triggered impulsive control with actuation delays

This study focused on the security synchronization problem for stochastic complex networks (SCNs) via event-triggered impulsive control (ETIC) with actuation delays. Firstly, incorporating the network topology and the Lyapunov function theory, a novel event-triggered mechanism (ETM) is devised, which accounts for actuation delays; Secondly, an ETM-based quantizer is introduced to optimize network resources, meantime, building upon this foundation, the Lipschitz–Razumikhin method is integrated with graph theory to establish a positive lower bound on the minimum event interval time, thereby preventing Zeno behavior; Additionally, some sufficient conditions are obtained to achieve global asymptotic synchronization of SCNs under quantization and deception attacks; Finally, a Chua’s circuit numerical simulation is employed to demonstrate the effectiveness of our theoretical findings.

Finite-Time Consensus of Second-Order Multi-Agent Systems via Event-Triggered Impulsive Control

In this study, the finite-time consensus problem of second-order multi-agent systems via event-triggered impulsive control is investigated. We leverage a novel approach that combines impulsive control, event-triggered communication, and finite-time stability theory. This successful combination achieves finite-time consensus while minimizing communication. In addition, the event-triggered condition determines both the impulsive instants and the update times for the finite-time control. Furthermore, it is shown that the Zeno-behavior and chattering phenomenon can be eliminated under our work. Numerical examples and simulations are provided to validate the effectiveness of the proposed control strategy.

Matrix Measure-Based Event-Triggered Impulsive Quasi-Synchronization on Coupled Neural Networks.

In this article, the quasi-synchronization for a kind of coupled neural networks with time-varying delays is investigated via a novel event-triggered impulsive control approach. In view of the randomly occurring uncertainties (ROUs) in the communication channels, the global quasi-synchronization for the coupled neural networks within a given error bound is considered instead of discussing the complete synchronization. A kind of distributed event-triggered impulsive controllers is presented with considering the Bernoulli stochastic variables based on ROUs, which works at each event-triggered impulsive instant. According to the matrix measure method and the Lyapunov stability theorem, several sufficient conditions for the realization of the quasi-synchronization are successfully derived. Combining with the mathematical methodology with the formula of variation of parameters and the comparison principle for the impulsive systems with time-varying delays, the convergence rate and the synchronization error bound are precisely estimated. Meanwhile, the Zeno behaviors could be eliminated in the coupled neural network with the proposed event-triggered function. Finally, a numerical example is presented to prove the results of theoretical analysis.

Quasi-synchronization of parameter mismatch drive-response systems: A self-triggered impulsive control strategy

The objective of this paper is to research the quasi-synchronization of parameter mismatch drive–response systems via a self-triggered impulsive control (STIC) strategy. In the proposed STIC strategy, the impulsive instants are determined by a carefully crafted self-triggered mechanism (STM). In contrast to the event-triggered impulsive control (ETIC), which continuously supervises an event-triggered condition to determine whether to generate an impulse, the proposed STIC strategy predicts the next impulsive instant using the last impulsive instant and measurable information, eliminating continuous event monitoring. By means of the presented STIC strategy, some sufficient quasi-synchronization conditions and error bound for parameter mismatch drive–response systems are obtained. Moreover, the Zeno-behavior can be eliminated for the impulsive instants. The effectiveness of the proposed STIC strategy is demonstrated through two numerical examples.

Event-triggered delayed impulsive control for functional differential systems on networks

This article investigates the stability of functional differential systems on networks adopting event-triggered multi-delayed impulsive control. We construct a new event-triggered mechanism (ETM) type using the Lyapunov function and the network topology. Combined with the ETM and multi-delayed impulsive control, in which the impulsive jumps are related to the current and past states, we propose a multi-delayed event-triggered impulsive control strategy. This controller will execute the control tasks only when the systems violate the preset ETM. In the view of the Razumikhin method and the graph theory, some criteria are given to avoiding Zeno behavior under this ETM and achieving exponential stability, which is related to the event-triggered parameters, network topology, and impulsive intensity. As an application of our theoretical results, a class of coupled oscillation systems is considered and numerical simulations are presented to verify the practicability and effectiveness.

Chaotic synchronization and fractal interpolation-based image encryption: exploring event-triggered impulsive control in variable-order fractional lur’e systems

Chaotic synchronization and fractal interpolation-based image encryption: exploring event-triggered impulsive control in variable-order fractional lur’e systems

Event-triggered impulsive control for second-order nonlinear multi-agent systems under DoS attacks

<abstract><p>We investigated impulsive consensus in second-order nonlinear multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. We consided scenarios where the communication network is subjected to DoS attacks, disrupting communication links and causing changes in the communication topology. An event-triggered impulsive control(ETIC) approach is proposed to flexibly address these issues. Additionally, an upper bound on the DoS attack period is introduced. Finally, a numerical example is given to verify the validity of the major results.</p></abstract>

Neuro-Optimal Event-Triggered Impulsive Control for Stochastic Systems via ADP.

This article presents a novel neural-network-based optimal event-triggered impulsive control method. First, a novel general-event-based impulsive transition matrix (GITM) is constructed to represent the probability distribution evolving characteristics regarding all system states across the impulsive actions, rather than the prefixed timing sequence. On the foundation of this GITM, the event-triggered impulsive adaptive dynamic programming (ETIADP) algorithm and its high-efficiency version (HEIADP) are developed to deal with the optimization problems for stochastic systems with event-triggered impulsive controls. It is shown that the obtained controller design scheme can reduce the computational and communication burden caused by updating the controller periodically. By analyzing the admissibility, monotonicity, and optimality properties of ETIADP and HEIADP, we further establish the approximation error bound of the neural networks to address the connection between the ideal and neural-network-based realizations of the present methods. It is proven that the iterative value functions of both the ETIADP and HEIADP algorithms fall in a small neighborhood of the optimum as the iteration index increases to infinity. By adopting a novel task synchronization mechanism, the proposed HEIADP algorithm fully utilizes the computing resources of multiprocessor systems (MPSs), while significantly reducing the memory requirement compared to traditional ADP approaches. Finally, we carry out a numerical study to show that the proposed methods can fulfill the desired goals.

Resilient Synchronization of Neural Networks Under DoS Attacks and Communication Delays via Event-Triggered Impulsive Control

Resilient Synchronization of Neural Networks Under DoS Attacks and Communication Delays via Event-Triggered Impulsive Control

Prescribed-Time Control of Switched Systems: An Event-Triggered Impulsive Control Approach

Prescribed-Time Control of Switched Systems: An Event-Triggered Impulsive Control Approach

Event-Triggered Impulsive Control for Complex Networks Under Stochastic Deception Attacks

Event-Triggered Impulsive Control for Complex Networks Under Stochastic Deception Attacks

Event-triggered impulsive observer with [formula omitted]-asymptotic gain for DC microgrids

This paper studies the problem of the state estimate of a class of DC microgrids with both disturbed states and disturbed outputs via event-triggered impulsive observer (ETIO). First, a mathematical model is established for such class of DC microgrids, and then the notion of impulsive observer including impulsive observer with K-asymptotic gain is proposed. Then, by using two Lyapunov-like functions, a scheme of event-triggered impulsive control (ETIC) via three layers of event-triggering conditions is designed for ETIO to track the state of the DC microgrid. And an algorithm is given for the implementation of ETIC in practice. The ETIC scheme is then extended to the sampling-based ETIC (S-ETIC) to reduce the calculation and improve the effectiveness of the ETIC. Both theoretical proofs and numerical simulations are given to show that the proposed ETIO via both ETIC and S-ETIC can track the state of the DC microgrid within K-asymptotic gain. Specifically, when the disturbance tends to zero, the tracking is accurate. Moreover, the simulation is given for comparisons between ETIO and other observers including the classic impulsive observer, Luenberger observer, sliding mode observer, and extended state observer. It is shown that the designed ETIO has advantages of lower impulse frequency, lower control cost, and smaller tracking error than the other observers.