Arnoldi-based model order reduction for linear systems with inhomogeneous initial conditions

Song, Qiu-Yan; Jiang, Yao‐Lin; Xiao, Zhi-Hua

doi:10.1016/j.jfranklin.2017.10.014

Cited by 9 publications

(1 citation statement)

References 29 publications

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Order By: Relevance

“…This approach is also applicable to second order systems with inhomogeneous initial conditions with the help of the superposition principle [29]. The time domain MOR techniques are modified by taking the initial data into the construction of projection matrices to ensure an accurate approximation in [30]. With the same spirit, these methods have been applied to more general systems, such as port-Hamiltonian systems and bilinear systems with non-zero initial conditions [31,32].…”

Section: Introductionmentioning

confidence: 99%

Spare Ordering Policy Model Based on Complex System Degradation Mechanism

et al. 2018

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Security service and effective perception of equipment becomes more and more important, especially for some high-end equipment complex system module degradation condition prediction and efficient spare ordering is the key to guarantee safe operation, improve service quality and reduce maintenance costs. In this paper, therefore, we analyze the characteristics of the complex system and propose an order policy model based on complex system degradation mechanism. The system degradation model is established based on the condition space feature matrix. The system ordering policy model is constructed using the system degradation model and spare random lead-time, whose decision variable is the placing an order time. Based on the proposed system ordering policy model there exists a finite and unique optimum placing an order time that minimizes the expected cost rate. Finally, a case study is presented to verify the effectiveness of the proposed system ordering policy model.

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