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Improving convergence in numerical analysis using observers - The wave-like equation case

Abstract : We propose an observer-based approach to circumvent the issue of unbounded approximation errors -- with respect to the length of the time window considered -- in the discretization of wave-like equations in bounded domains, which covers the cases of the wave equation per se and of linear elasticity as well as beam, plate and shell formulations, and so on. Namely, taking advantage of some measurements available on the system over time, we adopt a strategy inspired from sequential data assimilation and by which the discrete system is dynamically corrected using the discrepancy between the solution and the measurements. In addition to the classical cornerstones of numerical analysis made up by stability and consistency, we are thus led to incorporating a third crucial requirement pertaining to observability -- to be preserved through discretization. The latter property warrants exponential stability for the corrected dynamics, hence provides bounded approximation errors over time. Special care is needed to establish the required observability at the discrete level, in particular due to the fact that we focus on an original observer method adapted to measurements of the main variable, whereas measurements of the time-derivative -- admissible, of course, albeit less frequent in practical systems -- lead to a stability analysis in which existing results can be more directly applied. We also provide some detailed application examples with several such wave-like equations, and the corresponding numerical assessments illustrate the performance of our approach.
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Contributor : Dominique Chapelle Connect in order to contact the contributor
Submitted on : Thursday, March 1, 2012 - 2:18:41 PM
Last modification on : Thursday, August 25, 2022 - 3:47:53 AM
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Dominique Chapelle, Nicolae Cîndea, Philippe Moireau. Improving convergence in numerical analysis using observers - The wave-like equation case. Mathematical Models and Methods in Applied Sciences, 2012, 22 (12), ⟨10.1142/S0218202512500406⟩. ⟨inria-00621052v2⟩



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