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contributor authorTiwari, Sankalp
contributor authorShaik, Junaidvali
contributor authorVyasarayani, C. P.
date accessioned2024-04-24T22:45:43Z
date available2024-04-24T22:45:43Z
date copyright12/20/2023 12:00:00 AM
date issued2023
identifier issn1555-1415
identifier othercnd_019_02_021002.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4295830
description abstractDelay differential equations (DDEs) appear in many applications, and determining their stability is a challenging task that has received considerable attention. Numerous methods for stability determination of a given DDE exist in the literature. However, in practical scenarios it may be beneficial to be able to determine the stability of a delayed system based solely on its response to given inputs, without the need to consider the underlying governing DDE. In this work, we propose such a data-driven method, assuming only three things about the underlying DDE: (i) it is linear, (ii) its coefficients are either constant or time-periodic with a known fundamental period, and (iii) the largest delay is known. Our approach involves giving the first few functions of an orthonormal polynomial basis as input, and measuring/computing the corresponding responses to generate a state transition matrix M, whose largest eigenvalue determines the stability. We demonstrate the correctness, efficacy and convergence of our method by studying four candidate DDEs with differing features. We show that our approach is robust to noise, thereby establishing its suitability for practical applications, wherein measurement errors are unavoidable.
publisherThe American Society of Mechanical Engineers (ASME)
titleData Driven Approach to Determine Linear Stability of Delay Differential Equations Using Orthonormal History Functions
typeJournal Paper
journal volume19
journal issue2
journal titleJournal of Computational and Nonlinear Dynamics
identifier doi10.1115/1.4064251
journal fristpage21002-1
journal lastpage21002-11
page11
treeJournal of Computational and Nonlinear Dynamics:;2023:;volume( 019 ):;issue: 002
contenttypeFulltext


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