<i>l</i>₂–<i>l</i>∞ State Estimation for Persistent Dwell-Time Switched Coupled Networks Subject to Round-Robin Protocol

Shen, Hao; Xing, Mengping; Wu, Zheng‐Guang; Cao, Jinde; Huang, Tingwen

doi:10.1109/tnnls.2020.2995708

Cited by 38 publications

(13 citation statements)

References 47 publications

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“…In the follows, utilizing the Schur complement, and pre-and post-multiplying diag {I, I, I, R m } and its transpose, subsequently, with the employment of Lemma 2, one can attain that Ψ αβ m,µ(k) < 0 is satisfied with the establishment of conditions (19) and (20). Additionally, it can be observed obviously that condition (18) is equivalent to (14). It finishes the proof.…”

Section: Resultsmentioning

confidence: 57%

“…( ) As stated in [18], with the employment of PDT switching in the interval [t, k), the switching times A (t, k) satisfies…”

Section: B Node Dynamic With Switching Topologymentioning

confidence: 99%

“…In the study of the coupled networks, an important part is to acquire state information since it is indispensable when analyzing the relevant dynamics. Thus, state estimation serves a significant role in crack the nut that the practical node state information is often unavailable or only partially available, and abundant remarkable works have sprung up in past decades, see [18], [33], [34] and the references therein.…”

mentioning

confidence: 99%

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$\mathcal {H}_{\infty }$ State Estimation for PDT-Switched Coupled Neural Networks Under Round-Robin Protocol: A Cooperation-Competition-Based Mechanism

Shen

Song

Wang

et al. 2023

IEEE Trans. Netw. Sci. Eng.

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This paper is concentrated on the H∞ state estimation problem for switched coupled neural networks based on a Takagi-Sugeno fuzzy model. Notably, the time-variant network topology with alternate fast switchings and slow ones is described suitably by a persistent dwell-time rule, and the interactive dynamics with both cooperative properties and antagonistic ones among nodes are featured comprehensively by the switching signed graph. In view of the communication pressures brought by network-induced problems and the requirements in digital control, the round-robin protocol and logarithmic quantization are flexibly integrated for more transmission efficiency and fewer data collisions. Thereafter, by utilizing a relaxed multiple Lyapunov function method and some novel matrix process techniques, sufficient criteria guaranteeing the exponential stability in a globally uniform sense with a prescribed H∞ performance level of the estimation error system are established. Finally, the synthesized analysis of the proposed method is presented with an illustrative example.

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Section: Resultsmentioning

confidence: 57%

“…( ) As stated in [18], with the employment of PDT switching in the interval [t, k), the switching times A (t, k) satisfies…”

Section: B Node Dynamic With Switching Topologymentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

$\mathcal {H}_{\infty }$ State Estimation for PDT-Switched Coupled Neural Networks Under Round-Robin Protocol: A Cooperation-Competition-Based Mechanism

Shen

Song

Wang

et al. 2023

IEEE Trans. Netw. Sci. Eng.

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“…Assumption 1. [19] The nonlinear function g (⋅) meets the following sector-bounded condition below…”

Section: Markov Jump Coupled Networkmentioning

confidence: 99%

“…▪ Theorem 3. Given scalars a 1 > 0, a 2 > 0, > 1, > 0, matrix R > 0 and energy-to-peak norm̃> 0, the filtering error system (11) is mean-square FTB with respect to (a 1 , a 2 , N, R, ), if there exist scalars > 0, 1 > 0, an positive-definite symmetric matrix P m , and matrices  m ,  m ,  m , and Z m , such that conditions ( 17)- (19) and the following matrix inequality are feasible for ∀i ∈ S, m ∈ M…”

Section: Theorem 1 the Lyapunov Function Can Be Constructed As Belowmentioning

confidence: 99%

Finite‐time energy‐to‐peak quantized filtering for Markov jump networked systems under weighted try‐once‐discard protocol

Shen

Xia

et al. 2021

Intl J Robust & Nonlinear

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This work addresses the finite-time energy-to-peak filtering issue for networked systems subject to quantization effects and the weighted try-once-discard (WTOD) protocol, in which the random changes of coupling connections are governed by a Markov chain. To avoid the conflict in data transmission, the WTOD protocol is introduced to the communication between the sensor node and the filter, which guarantees that just one sensor node has access to send data at each transmission instant. In addition, the quantizer is employed to improve the reliability of data transmission. The objective of this article is to construct a filter such that the filtering error system satisfies the requirements of both the finite-time boundary and the specified energy-to-peak performance. Based on the Kronecker product, the Lyapunov stability theory and an improved matrix decoupling method, some sufficient conditions are established through disposing of convex optimization issues. Ultimately, the availability of the designed filter is illustrated via a numerical example. K E Y W O R D Senergy-to-peak filtering, finite-time boundary, Markov jump networked systems, weighted try-once-discard protocol

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Minimum‐variance recursive state estimation for complex networks with stochastic switching topologies and random quantization under try‐once‐discard protocol

et al. 2022

Adaptive Control & Signal

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SummaryThis article is concerned with the issue of minimum‐variance recursive state estimation (MVRSE) for a class of nonlinear dynamical complex networks (NDCNs) with stochastic switching topologies and random quantization under the try‐once‐discard (TOD) protocol. Two sequences of Bernoulli distributed random variables with given occurrence probabilities are utilized to characterize the stochastic switching manners of network topologies and the randomly occurring quantized output measurements, where the quantization effects are portrayed by the uniform quantizer. Moreover, the TOD protocol is adopted to arrange the order of the information transmission of network nodes so as to alleviate the communication burden and mitigate the network congestions. The focus of the MVRSE issue is to develop a novel state estimation algorithm such that, for all stochastic switching topologies, random quantization effects and TOD protocol, an optimized upper bound of the estimation error covariance is guaranteed by properly designing the estimator gain. In addition, the theoretical proof is derived, which illustrates that the state estimation error is exponentially mean‐square bounded under certain conditions. Meanwhile, we also present the related theoretical analysis, which discusses the impact caused by random quantization. Finally, a numerical experiment is utilized to show the validity of the novel MVRSE approach.

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l₂–l∞ State Estimation for Persistent Dwell-Time Switched Coupled Networks Subject to Round-Robin Protocol

Cited by 38 publications

References 47 publications

$\mathcal {H}_{\infty }$ State Estimation for PDT-Switched Coupled Neural Networks Under Round-Robin Protocol: A Cooperation-Competition-Based Mechanism

$\mathcal {H}_{\infty }$ State Estimation for PDT-Switched Coupled Neural Networks Under Round-Robin Protocol: A Cooperation-Competition-Based Mechanism

Finite‐time energy‐to‐peak quantized filtering for Markov jump networked systems under weighted try‐once‐discard protocol

Minimum‐variance recursive state estimation for complex networks with stochastic switching topologies and random quantization under try‐once‐discard protocol

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