Generalized Dissipativity State Estimation of Delayed Static Neural Networks Based on a Proportional-Integral Estimator With Exponential Gain Term

This paper is concerned with the robust H ∞ load frequency control (LFC) of power systems with two time delays in the presence of load disturbance. Firstly, the original power systems with the proportional-integral (PI)-type LFC are converted into an output feedback control system with two time delays. Secondly, an improved reciprocally convex inequality is proposed, and a less conservative robust H ∞ criterion is derived, which can be used to design the PI-type LFC with robust H ∞ performance. Then, based on the robust H ∞ criterion, an algorithm is provided to obtain the PI-type LFC gain and the time delay margin, which effectively convert the coupled nonlinear terms into linear items without solving the inverse of the matrix with row full rank. Finally, simulations are shown to verify the superiority of the presented method.

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“…Then, from (14) to (16), by applying the Jensen integral inequality 25,26 again, one has

\overset{V}{true} ((), t) \leq δ^{T} ((), t) ((), Ω_{1} - Ω_{2} Ω_{3}^{- 1} Ω_{2}^{T}) δ ((), t) - y^{T} ((), t) y ((), t) + γ^{2} ω^{T} ((), t) ω ((), t)

where

δ ((), t) = {[x^{T} (t), x^{T} (t - τ_{f}), x^{T} (t - τ (t)), x^{T} (t - τ_{d}), ω^{T} (t)]}^{T}

.…”

Section: Resultsmentioning

confidence: 99%

Robust load frequency control of power systems with two time delays

Tan

Shi

Liu

et al. 2021

Int Trans Electr Energ Syst

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“…(3) A stability criterion is established to guarantee FTS based on the proposed technique lemma. In the future, how to extend the method proposed in this paper to the study of state estimation and control problems, see [3,5,8] are the further research topics.…”

Section: Discussionmentioning

confidence: 99%

“…With the deepening research on biological network, neural network, gene network and other excellent achievements have been produced in recent years [1][2][3][4][5][6]. Especially, as a powerful research tool for cell recognition, metabolism and signal transduction in the growth and reproduction processes of organisms, a mess of experts and scholars pay a widely sight of genetic regulatory networks (GRNs) in the field of biomedical and bioengineering [1,2].…”

Section: Introductionmentioning

confidence: 99%

Stability analysis of genetic regulatory networks via a linear parameterization approach

Xiao

Wang

2021

Complex Intell. Syst.

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This paper investigates the problem of finite-time stability (FTS) for a class of delayed genetic regulatory networks with reaction-diffusion terms. In order to fully utilize the system information, a linear parameterization method is proposed. Firstly, by applying the Lagrange’s mean-value theorem, the linear parameterization method is applied to transform the nonlinear system into a linear one with time-varying bounded uncertain terms. Secondly, a new generalized convex combination lemma is proposed to dispose the relationship of bounded uncertainties with respect to their boundaries. Thirdly, sufficient conditions are established to ensure the FTS by resorting to Lyapunov Krasovskii theory, convex combination technique, Jensen’s inequality, linear matrix inequality, etc. Finally, the simulation verifications indicate the validity of the theoretical results.

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“…Model predictive control, 2 fuzzy control, 3 and PI control 4 have been extensively used in LFC. In contrast, PI control has better robustness and does not depend on the accurate model of the power system, which is the most widely implemented control method in the current industrial field 5‐23 …”

Section: Introductionmentioning

confidence: 99%

“…In deregulated electricity environment, open communication links bring some network‐induced challenge, including communication delays and bandwidth limitation, etc. On the one hand, the presence of communication delays may deteriorate the performance of the system and even cause instability 5‐7 . Thus, researches on delay‐dependent LFC of power system have long been an active issue 8‐11 .…”

Section: Introductionmentioning

confidence: 99%

Dynamic event‐triggered H_∞ load frequency control for multi‐area power systems with communication delays

Wang

Tian

2021

Intl J Robust & Nonlinear

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This paper investigates dynamic event‐triggered H∞ load frequency control for multi‐area power systems with communication delays. A novel co‐design method of trigger parameters and H∞ controller based on output feedback is proposed. Unlike routine multiplication operations, this method eliminates rank constraints on the input and output matrices, and avoids the processing of nonlinear terms related to the trigger parameters. Furthermore, under the presented dynamic event‐triggered mechanism, the threshold parameters are dynamically regulated according to the dynamic variation of the system. Therefore, the average data releasing rate can be adjusted in real time to better coordinate the use of network bandwidth resources and requirements of system dynamic performance. Specially, the usage of the infinite‐series‐based inequality and reciprocally convex combination inequality effectively reduces conservatism of the criteria. Finally, some simulations and related comparisons are carried out to demonstrate superiorities of the proposed method.

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Generalized Dissipativity State Estimation of Delayed Static Neural Networks Based on a Proportional-Integral Estimator With Exponential Gain Term

Cited by 40 publications

References 16 publications

Robust load frequency control of power systems with two time delays

Robust load frequency control of power systems with two time delays

Stability analysis of genetic regulatory networks via a linear parameterization approach

Dynamic event‐triggered H_∞ load frequency control for multi‐area power systems with communication delays

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Generalized Dissipativity State Estimation of Delayed Static Neural Networks Based on a Proportional-Integral Estimator With Exponential Gain Term

Cited by 40 publications

References 16 publications

Robust load frequency control of power systems with two time delays

Robust load frequency control of power systems with two time delays

Stability analysis of genetic regulatory networks via a linear parameterization approach

Dynamic event‐triggered H∞ load frequency control for multi‐area power systems with communication delays

Contact Info

Product

Resources

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Dynamic event‐triggered H_∞ load frequency control for multi‐area power systems with communication delays