Synchronization Analysis for Complex Dynamical Networks With Coupling Delay via Event-Triggered Delayed Impulsive Control

Lv, Xiaoxiao; Cao, Jinde; Li, Xiaodi; Abdel‐Aty, Mahmoud; Al-Juboori, Udai Ali

doi:10.1109/tcyb.2020.2974315

Cited by 67 publications

(27 citation statements)

References 40 publications

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“…In [38] the controller is only upgraded for each agent if those statedependent errors reach a tolerable limit and the control inputs are performed by the actor only at event triggering impulsive instants and in [46], the controller updates are event-based for each agent and will only be triggered at their own event times. In [13], by the combination of delayed impulsive control with the event-triggering mechanism, a the novel event-triggered delayed impulsive control is formulated using the quadratic Lyapunov function. Between them, event-triggering instants are produced when the event-based impulsive control strategy is violate, and delayed impulsive control is only applied at eventtriggering instants.…”

Section: Network Modelmentioning

confidence: 99%

“…Remark 1. In several research work [13,22,[38][39][40][41][42][43][44], signal function is implemented to achieve full event based control. This implies that we must always detect the state information of each system.…”

Section: Network Modelmentioning

confidence: 99%

“…The eventbased control law that determines when the sampling is performed quickly or slowly and whether the sampling information needs to be transmitted for control updates. The approach was introduced to networks, and distributed event-triggered control techniques which were proposed in [13,38,[40][41][42]46]. In [38] the controller is only upgraded for each agent if those statedependent errors reach a tolerable limit and the control inputs are performed by the actor only at event triggering impulsive instants and in [46], the controller updates are event-based for each agent and will only be triggered at their own event times.…”

Section: Network Modelmentioning

confidence: 99%

“…Moreover, according to various topological structures, the NNs system has different dynamical behaviours such as the stability, synchronisation and bifurcations. As one of the classical phenomenon of NNs, synchronisation analysis has been extensively studied in [2][3][4][12][13][14][15]. It is noticeable that the results of all synchronisation or anti-synchronisation has been mentioned in the works concerned with co-operative networks.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quasi‐bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event‐triggered impulsive control strategy

Udhayakumar

Rihan

et al. 2021

IET Control Theory & Appl

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The central concern of this paper is to study leader-following quasi-bipartite synchronisation of a multiple inertial signed neural networks with varying time-delay by utilising distributed event-triggered impulsive control scheme, where connections between adjacent nodes of the neural networks either positive or negative. The second-order neural networks, called inertial neural networks, can be transformed into differential equations of first-order by implementing suitable variable substitution. Under certain hypothesis about the node dynamics, signed graph theory and balanced topology of networks, some conditions are derived in terms of lower-dimensional linear matrix inequalities (LMIs) to achieve leader-following quasi-bipartite synchronisation. In addition, a basic algebraic condition is derived to estimate the theoretical upper bound for the error node. Finally, some numerical simulations are provided to illustrate the correctness of the theoretical results.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Network Modelmentioning

confidence: 99%

Section: Network Modelmentioning

confidence: 99%

Section: Network Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quasi‐bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event‐triggered impulsive control strategy

Udhayakumar

Rihan

et al. 2021

IET Control Theory & Appl

Self Cite

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“…Very recently, ET impulsive control strategy has been becoming an emergent hot topic about synchronisation of multisystem networks (see [32][33][34][35][36][37][38] and references therein), which inherit the respective merits of ET control and impulsive control. Comparing with general impulsive control, the ET impulsive strategy is more flexible as the impulse instants are determined by ET condition.…”

Section: Introductionmentioning

confidence: 99%

Synchronisation of multiple neural networks via event‐triggered time‐varying delay hybrid impulsive control

Ruan

Feng

et al. 2021

IET Control Theory & Appl

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This article discusses the exponential synchronisation problem for multiple neural networks with time-varying delay and a more general non-Laplacian coupling matrix is considered. To reduce the redundant communication, two event-based time-varying delay hybrid impulsive control schemes are proposed with static event-triggered condition and dynamic event-triggered condition. These novel control schemes neatly combine the eventtriggered coupling strategy with the time-varying delay hybrid impulsive control, where the impulsive instant is only determined by the specified event-triggered condition. Moreover, a delay impulsive differential inequality is established to discuss the synchronisation problem for controlled multiple neural networks. By using Stolz's theorem and introducing the average event-triggered delay impulsive gain, some less conservative sufficient conditions are derived to assure the stability of the time-varying delay multiple neural networks. Furthermore, the Zeno behaviour can be eliminated effectively and the consumption of the computing resources can be reduced. Finally, some examples are given to verify the superiority of the results. First, a static event-triggered time-varying delay hybrid impulsive control scheme was proposed to lessen the communication burden. Then, a time-varying delay impulsive differential inequality was established to guarantee the synchronisation of multiple neural networks. Moreover, the authors also discussed the issue that continuously triggering and sampling can be excluded.

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Bipartite synchronization of multi‐agent systems under deception attacks via pinning delayed‐impulsive control

Dai

Guo

et al. 2023

Intl J Robust & Nonlinear

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This article aims to investigate the bipartite synchronization problem of multi-agent systems (MASs) under deception attacks. A pinning delayed-impulsive control scheme is proposed to solve the synchronization of MASs under deception attacks that modify the transmitted data information and destroy the data integrity. The time delay can have a gain effect on the stability of the system by using time delay utilization technology. By selecting the appropriate time delay parameters, the convergence speed of the system is effectively improved. Furthermore, cooperative and competitive interactions between agents are considered. Sufficient conditions of the bipartite mean-square bounded synchronization of MASs under deception attacks are theoretically obtained. Finally, the designed numerical simulations illustrate the correctness and effectiveness of our results.

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Synchronization Analysis for Complex Dynamical Networks With Coupling Delay via Event-Triggered Delayed Impulsive Control

Cited by 67 publications

References 40 publications

Quasi‐bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event‐triggered impulsive control strategy

Quasi‐bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event‐triggered impulsive control strategy

Synchronisation of multiple neural networks via event‐triggered time‐varying delay hybrid impulsive control

Bipartite synchronization of multi‐agent systems under deception attacks via pinning delayed‐impulsive control

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