Local <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="mml1" display="inline" overflow="scroll" altimg="si1.gif"><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:math> synchronization of uncertain complex networks via non-fragile state feedback control

Luo, Yiping; Deng, Fei; Ling, Zhaomin; Cheng, Zifeng

doi:10.1016/j.matcom.2018.07.009

Cited by 14 publications

(5 citation statements)

References 20 publications

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“…Chaos control associated with complex phenomena has been identified in actual supply chain systems. Numerous researchers have explored control and synchronization methods to characterize these systems in the literature such as robust control [9], delayed feedback control [17], adaptive sliding mode control [18], ANN [19], ANFIS [20], Robust H∞ control [21], tracking control [22], stochastic fixed-time tracking control [23], fuzzy neural network control [24], and nonlinear control [25].…”

Section: Introductionmentioning

confidence: 99%

Dynamical Analysis and Sliding Mode Controller for the New 4D Chaotic Supply Chain Model Based on the Product Received by the Customer

Johansyah,

Vaidyanathan,

Sambas

et al. 2024

Mathematics

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Supply chains comprise various interconnected components like suppliers, manufacturers, distributors, retailers, and customers, each with unique variables and interactions. Managing dynamic supply chains is highly challenging, particularly when considering various sources of risk factors. This paper extensively explores dynamical analysis and multistability analysis to understand nonlinear behaviors and pinpoint potential risks within supply chains. Different phase portraits are used to demonstrate the impact of various factors such as transportation risk, quality risk, distortion, contingency reserves, and safety stock on both customers and retailers. We introduced a sliding mode control method that computes the sliding surface and its derivative by considering the error and its derivative. The equivalent control law based on the sliding surface and its derivative is derived and validated for control purposes. Our results show that the controller SMC can significantly enhance supply chain stability and efficiency. This research provides a robust framework for understanding complex supply chain dynamics and offers practical solutions to enhance supply chain resilience and flexibility.

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Section: Introductionmentioning

confidence: 99%

Dynamical Analysis and Sliding Mode Controller for the New 4D Chaotic Supply Chain Model Based on the Product Received by the Customer

Johansyah,

Vaidyanathan,

Sambas

et al. 2024

Mathematics

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“…Nevertheless, when the nonlinear node system has strong high-order nonlinearity, this network system cannot achieve global synchronization, even if the external controller is adopted and the chosen control gain is sufficiently large. Under this circumstance, the local synchronization is introduced and some results with respect to the local synchronization of CNs were acquired in [17][18][19][20][21][22]. From the aforementioned existing literature [17][18][19], it can be known that the strong nonlinearity is considered relatively rarely, and the influence of initial values on synchronization realization is also ignored.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Domain of Attraction on Controlled Nonlinear Neutral Complex Networks via Razumikhin Approach

Yu,

Song

2024

Symmetry

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This paper is devoted to dealing with the issue of the estimation of the domain of attraction (DOA) for highly nonlinear neutral complex networks (HNNCNs) with time delays. Firstly, by the Razumikhin approach, we establish several novel lemmas on the estimation of DOA for highly nonlinear neutral differential systems. The cases of bounded non-differentiable delays and unbounded proportional delays are discussed, respectively. Subsequently, by utilizing the proposed lemmas, combining the Lyapunov stability theory and inequality technique, the estimation of DOA on HNNCNs with bounded delays or proportional delays is derived when the chosen control gain is sufficiently large. If initial values start from DOA, then the states of systems will exponentially or polynomially converge to the equilibrium point, which means that the local exponential or polynomial synchronization of HNNCNs is realized. Additionally, the weighted outer-coupling matrix of complex networks is not required to be symmetric, which means that the derived results can be applied to both the undirected networks and directed networks. Finally, several numerical examples are provided to illustrate the feasibility of theoretical findings.

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“…In order to reflect the complexity of the actual dynamical system, there is a need to consider the parameter uncertainties due to the changes of internal structure and environmental impacts, which can not be ignored and estimated with difficulties (Luo et al, 2019). In order to facilitate the theoretical research from mathematics, the parameters uncertainties of the system model have been well discussed as in Bougofa et al (2020) and Locke et al (2020).…”

Section: Introductionmentioning

confidence: 99%

State estimation via prediction-based scheme for linear time-varying uncertain networks with communication transmission delays and stochastic coupling

Jia

et al. 2021

Systems Science & Control Engineering

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Local H∞ synchronization of uncertain complex networks via non-fragile state feedback control

Cited by 14 publications

References 20 publications

Dynamical Analysis and Sliding Mode Controller for the New 4D Chaotic Supply Chain Model Based on the Product Received by the Customer

Dynamical Analysis and Sliding Mode Controller for the New 4D Chaotic Supply Chain Model Based on the Product Received by the Customer

Estimation of the Domain of Attraction on Controlled Nonlinear Neutral Complex Networks via Razumikhin Approach

State estimation via prediction-based scheme for linear time-varying uncertain networks with communication transmission delays and stochastic coupling

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