Inverse problem for a parabolic system with two components by measurements of one component (original) (raw)

Inverse source problem and null controllability for multidimensional parabolic operators of Grushin type

Inverse Problems, 2014

The approach to Lipschitz stability for uniformly parabolic equations introduced by Imanuvilov and Yamamoto in 1998, based on Carleman estimates, seems hard to apply to the case of Grushin-type operators of interest to this paper. Indeed, such estimates are still missing for parabolic operators degenerating in the interior of the space domain. Nevertheless, we are able to prove Lipschitz stability results for inverse source problems for such operators, with locally distributed measurements in arbitrary space dimension. For this purpose, we follow a mixed strategy which combines the appraoch due to Lebeau and Robbiano, relying on Fourier decomposition, with Carleman inequalities for heat equations with nonsmooth coefficients (solved by the Fourier modes). As a corollary, we obtain a direct proof of the observability of multidimensional Grushintype parabolic equations, with locally distributed observations-which is equivalent to null controllability with locally distributed controls.

Recent results on the controllability of linear coupled parabolic problems: A survey

2011

This paper tries to summarize recent results on the controllability of systems of (several) parabolic equations. The emphasis is placed on the extension of the Kalman rank condition (for finite dimensional systems of differential equations) to parabolic systems. This question is itself tied with the proof of global Carleman estimates for systems and leads to a wide field of open problems.

Inverse problem for a coupled parabolic system with discontinuous conductivities: One-dimensional case

Inverse Problems and Imaging, 2013

We study the inverse problem of the simultaneous identification of two discontinuous diffusion coefficients for a one-dimensional coupled parabolic system with the observation of only one component. The stability result for the diffusion coefficients is obtained by a Carleman-type estimate. Results from numerical experiments in the one-dimensional case are reported, suggesting that the method makes possible to recover discontinuous diffusion coefficients.

Global Carleman Inequalities for Parabolic Systems and Applications to Controllability

Siam Journal on Control and Optimization, 2006

This paper has been conceived as an overview on the controllability properties of some relevant (linear and nonlinear) parabolic systems. Specifically, we deal with the null controllability and the exact controllability to the trajectories. We try to explain the role played by the observability inequalities in this context and the need of global Carleman estimates. We also recall the main ideas used to overcome the difficulties motivated by nonlinearities. First, we considered the classical heat equation with Dirichlet conditions and distributed controls. Then we analyze recent extensions to other linear and semilinear parabolic systems and/or boundary controls. Finally, we review the controllability properties for the Stokes and Navier-Stokes equations that are known to date. In this context, we have paid special attention to obtaining the necessary Carleman estimates. Some open questions are mentioned throughout the paper. We hope that this unified presentation will be useful for those researchers interested in the field.

Stability estimate for a hyperbolic inverse problem with time-dependent coefficient

Inverse Problems, 2015

We study the stability in the inverse problem of determining the time dependent zeroth-order coefficient q(t, x) arising in the wave equation, from boundary observations. We derive, in dimension n ≥2 , a log-type stability estimate in the determination of q from the Dirichlet-to-Neumann map, in a subset of our domain assuming that it is known outside this subset. Moreover, we prove that we can extend this result to the determination of q in a larger region, and then in the whole domain provided that we have much more data.