Topology identification for fractional complex networks with synchronization in finite time based on adaptive observers and event-triggered control

Bai, Jing; Wu, Huaiqin; Cao, Jinde

doi:10.1016/j.neucom.2022.07.023

Cited by 15 publications

(11 citation statements)

References 38 publications

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“…where the parameters α, d, are same as that in the drive network (25). In addition, the update law of the observer bi j (t) is described by…”

Section: Exclusion Of Zeno Phenomenonmentioning

confidence: 99%

“…2 (a) and (b), respectively. It is easy to see that, network (25) and (26) can not achieve the synchronization, and the topology of network (25) can not also be identified in finite time.…”

Section: Exclusion Of Zeno Phenomenonmentioning

confidence: 99%

“…Let t 0 = 0. Take the initial values x 1 (0) = (−1.320, −2.140, 1.035) T , x 2 (0) = (−3.070, −1.852, −2.041) T , x 3 (0) = (−1.331, 2.508, −0.901) T for network (25), and The setting time T (e i (t 0 )) is calculated as T (e i (t 0 )) = 3.3156 based Theorem 1. The corresponding simulation results are shown in Fig.…”

Section: Exclusion Of Zeno Phenomenonmentioning

confidence: 99%

“…To address the drawback, the eventtriggered control (ETC) determined by static rule is proposed, and some results about the synchronization of CDNs were obtained by applying static ETC . see [22][23][24][25][26]. In static ETC, information is updated only when the threshold is less than or equal to the measurement error.…”

Section: Introductionmentioning

confidence: 99%

“…2) An topology observer and a DETM are designed to realize the topology identification and synchronization for FSPCNs. Compared with the control methods used in [23,25], the control strategy adopted in this paper can save resource more efficiently.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An Observer-Based Topology Identification and Synchronization in Finite Time for Fractional Singularly Perturbed Complex Networks via Dynamic Event-Triggered Control

Wang,

Wu,

Cao

2024

Neural Process Lett

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This paper investigates the topology identification and synchronization in finite time for fractional singularly perturbed complex networks (FSPCNs). Firstly, a convergence principle is developed for continuously differential functions. Secondly, a dynamic event-triggered mechanism (DETM) is designed to achieve the network synchronization, and a topology observer is developed to identify the network topology. Thirdly, under the designed DETM, by constructing a Lyapunov functional and applying the inequality analysis technique, the topology identification and synchronization condition in finite time is established in the forms of the matrix inequality. In addition, it is proved that the Zeno behavior can be effectively excluded. Finally, the effectiveness of the main results is verified by an application example.

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“…where the parameters α, d, are same as that in the drive network (25). In addition, the update law of the observer bi j (t) is described by…”

Section: Exclusion Of Zeno Phenomenonmentioning

confidence: 99%

“…2 (a) and (b), respectively. It is easy to see that, network (25) and (26) can not achieve the synchronization, and the topology of network (25) can not also be identified in finite time.…”

Section: Exclusion Of Zeno Phenomenonmentioning

confidence: 99%

Section: Exclusion Of Zeno Phenomenonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Observer-Based Topology Identification and Synchronization in Finite Time for Fractional Singularly Perturbed Complex Networks via Dynamic Event-Triggered Control

Wang,

Wu,

Cao

2024

Neural Process Lett

Self Cite

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Exponential Synchronization of Complex Dynamic Networks with Time Delay and Uncertainty via Adaptive Event-Triggered Control

Zhao,

2024

Neural Process Lett

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In this paper, exponential synchronization problem of uncertain complex dynamic networks with time delay is studied via adaptive event-triggered control. Considering the influence of external environment, a new dynamic event-triggered mechanism is proposed, in order to reduce the transmission signal among nodes and reduce the consumption of communication resources. Moreover, in the proposed control mechanism, the controller is adaptive, that is, it only works when the triggering conditions are satisfied. Then, according to the designed adaptive event-triggered control strategy, the sufficient conditions for exponential synchronization are obtained by using Lyapunov functions and inequality technique. In addition, it is proved that the system can avoid Zeno behavior. At last, using two examples to verify the feasibility of the results.

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Topology Identification for Networked Piecewise-smooth Systems With Multiple Weight Couplings Based a Novel Fixed-time Synchronization Approach

Hou

2024

Int. J. Control Autom. Syst.

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Topology identification for fractional complex networks with synchronization in finite time based on adaptive observers and event-triggered control

Cited by 15 publications

References 38 publications

An Observer-Based Topology Identification and Synchronization in Finite Time for Fractional Singularly Perturbed Complex Networks via Dynamic Event-Triggered Control

An Observer-Based Topology Identification and Synchronization in Finite Time for Fractional Singularly Perturbed Complex Networks via Dynamic Event-Triggered Control

Exponential Synchronization of Complex Dynamic Networks with Time Delay and Uncertainty via Adaptive Event-Triggered Control

Topology Identification for Networked Piecewise-smooth Systems With Multiple Weight Couplings Based a Novel Fixed-time Synchronization Approach

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