Dynamic event-triggered <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si10.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> state estimation for delayed complex networks with randomly occurring nonlinearities

In this paper, the dynamic event-based recursive filtering problem is studied for multirate systems over sensor networks. The state update rate of the plant and the sampling rate of the sensors are allowed to be different in order to reflect the multirate sampling strategy. Moreover, the phenomenon of integral measurements is considered to cater for the real engineering practice. To reduce unnecessary data transmissions, the dynamic event-based mechanism is implemented in the communication channels among sensor nodes. The purpose of this paper is to design a distributed recursive filtering scheme such that, under the influence of the integral measurements, the multi-rate sampling, and the dynamic event-based mechanism, there exists a minimal upper bound on the filtering error covariance. An upper bound on the filtering error covariance is first derived by solving a matrix Riccati equation, and then minimized at each sampling instant by choosing appropriate filter gains. Comprehensive simulations are conducted on a numerical example and a practical example to show the effectiveness and superiority of the proposed dynamic event-based recursive filtering scheme.

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“…In the future, we will extend the results to other systems, that is, fuzzy systems, 43,44 complex networks, 45 and neural networks. [46][47][48]…”

Section: F I G U R Ementioning

confidence: 85%

Dynamic event‐based recursive filtering for multirate systems with integral measurements over sensor networks

Shen

Wang

Dong

et al. 2021

Intl J Robust & Nonlinear

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“…For the case that 𝜔(k) = 0, from ( 27) and ( 30), the constraints (10) can also be guaranteed for all initial conditions 𝜙(k) satisfying V 𝜎(0) (0) ≤ 1∕𝜛. Meanwhile, from (26), we have the following relation:…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, the embedding of communication networks in control systems have brought about certain imperfections (e.g., packet dropouts, communication delays, and signal quantization) which result mainly from inherent limited bandwidth. [23][24][25][26][27][28][29][30][31] For network with limited bandwidth, a typical way of preventing networked-induced phenomena is to deploy communication protocols so as to facilitate multiple (and simultaneous) signal transmissions. According to the popularity, three types of communication protocols have been adopted in industry applications, that is, round-robin (RR) protocol, try-once-discard (TOD) protocol, and random access (RA) protocol.…”

Section: Introductionmentioning

confidence: 99%

Dynamic output‐feedback control for discrete time‐delayed systems with actuator saturations under round‐robin communication protocol

Chen

Wang

Alsaadi

et al. 2021

Intl J Robust & Nonlinear

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In this article, the dynamic output-feedback H ∞ control problem is investigated for discrete-time state-delay systems subject to exogenous disturbances and actuator saturations under the round-robin communication protocol. Using the switched system approach, the Lyapunov-Krasovskii functional and the modified sector condition, sufficient conditions are first obtained under which the closed-loop systems can achieve some desirable performance indices such as the boundedness, the H ∞ performance and the stability in the absence of disturbances. Then, the controller is explicitly characterized by means of the solvability of linear matrix inequalities. For the case without time delays, the corresponding conditions are also presented. Subsequently, the optimization problems about the performance indices are discussed. Finally, the benefit and effectiveness of the proposed results are specifically illustrated via two simulation examples.

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“…Recently, dynamical complex networks (DCNs) have proven to be a persistent focus of research owing to their potential applications in cyber-physical systems, biological networks, power grid networks, social networks, and so forth. [1][2][3][4][5][6] Generally, the successes of these applications are largely dependent on the true states of the network nodes in DCNs. Due to reasons such as noisy environment, large scale, and tight coupling, the state information of DCNs is usually immeasurable or only partially available in practice.…”

Section: Introductionmentioning

confidence: 99%

Centralized moving‐horizon estimation for a class of nonlinear dynamical complex networks under event‐triggered transmission scheme

Gao

Wang

Sheng

et al. 2022

Intl J Robust & Nonlinear

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This article is concerned with the problem of event-triggered centralized moving-horizon state estimation for a class of nonlinear dynamical complex networks. An event-triggered scheme is employed to reduce unnecessary data transmissions between sensors and estimators, where the signal is transmitted only when certain condition is violated. By treating sector-bounded nonlinearities as certain sector-bounded uncertainties, the addressed centralized moving-horizon estimation problem is transformed into a regularized robust least-squares problem that can be effectively solved via existing convex optimization algorithms. Moreover, a sufficient condition is derived to guarantee the exponentially ultimate boundedness of the estimation error, and an upper bound of the estimation error is also presented. Finally, a numerical example is provided to demonstrate the feasibility and efficiency of the proposed estimator design method.

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Dynamic event-triggered H∞ state estimation for delayed complex networks with randomly occurring nonlinearities

Cited by 37 publications

References 38 publications

Dynamic event‐based recursive filtering for multirate systems with integral measurements over sensor networks

Dynamic event‐based recursive filtering for multirate systems with integral measurements over sensor networks

Dynamic output‐feedback control for discrete time‐delayed systems with actuator saturations under round‐robin communication protocol

Centralized moving‐horizon estimation for a class of nonlinear dynamical complex networks under event‐triggered transmission scheme

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