Sparse source identification of linear diffusion–advection equations by adjoint methods

Monge A, Zuazua E (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Systems & Control Letters Elsevier

Book Volume: 145

Article Number: 104801

DOI: 10.1016/j.sysconle.2020.104801

Abstract

We present an algorithm for the time-inversion of diffusion–advection equations, based on the adjoint methodology. Given a final state distribution our main aim is to recover sparse initial conditions, constituted by a finite combination of Kronecker deltas, identifying their location and mass. We discuss the strengths of the adjoint machinery and the difficulties that are to be faced, in particular when the diffusivity coefficient or the time horizon is large.

Authors with CRIS profile

Enrique Zuazua Iriondo Lehrstuhl für Dynamics, Control, Machine Learning and Numerics (Alexander von Humboldt-Professur)

Involved external institutions

University of Deusto / Universidad de Deusto ES Spain (ES)

How to cite

APA:

Monge, A., & Zuazua, E. (2020). Sparse source identification of linear diffusion–advection equations by adjoint methods. Systems & Control Letters, 145. https://dx.doi.org/10.1016/j.sysconle.2020.104801

MLA:

Monge, Azahar, and Enrique Zuazua. "Sparse source identification of linear diffusion–advection equations by adjoint methods." Systems & Control Letters 145 (2020).

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