J. Travaux-publiés-revues-internationales, H. Schorsch, M. Garnier, P. C. Gilson, and . Young, Instrumental variable methods for identifying partial differential equation models, International Journal of Control, 2013.

J. Congrès-internationaux-avec-comité-de-lecture, H. Schorsch, M. Garnier, and . Gilson, Instrumental variable methods for identifying partial differential equation models of distributed parameter systems, IFAC Symposium on System Identification, pp.840-845, 2012.

J. Schorsch, M. Gilson, V. Laurain, and H. Garnier, Identification of LPV partial differential equation models, 52nd IEEE Conference on Decision and Control, 2013.
DOI : 10.1109/CDC.2013.6760590

URL : https://hal.archives-ouvertes.fr/hal-00861956

?. Pour-des-congrès-internationaux, :. J. Schorsch, H. Garnier, and M. Gilson, Instrumental variable methods for identifying partial differential equation models of distributed parameter systems, IFAC Symposium on System Identification, pp.840-845, 2012.

A. [. Ali, H. Ali, H. Abbas, and . Werner, Identification of Box-Jenkins models for Parameter-Varying Spatially Interconnected systems, Proceedings of the 2011 American Control Conference, pp.145-150, 2011.
DOI : 10.1109/ACC.2011.5991133

M. Ali, A. Ali, S. S. Chughtai, and H. Werner, Consistent identification of spatially interconnected systems, Proceedings of the 2011 American Control Conference, pp.3583-3588, 2011.
DOI : 10.1109/ACC.2011.5991360

]. M. Acw10a, S. S. Ali, H. Chughtai, and . Werner, Consistent identification of two-dimensional systems, American Control Conference Baltimore USA, pp.3464-3469, 2010.

M. Ali, S. S. Chughtai, and H. Werner, Identification of LPV models for spatially varying interconnected systems, Proceedings of the 2010 American Control Conference, pp.3889-3894, 2010.
DOI : 10.1109/ACC.2010.5530658

]. A. Ame72 and . Ames, Nonlinear partial differential equations in engineering Mathematics in science and engineering : a series in monographs and textbooks, 1972.

J. [. Battaglia, . Ch, L. L. Batsale, and . Lay, Utilisation de mod??les d'identification non entiers pour la r??solution de probl??mes inverses en conduction, International Journal of Thermal Sciences, vol.39, issue.3, pp.374-389, 2000.
DOI : 10.1016/S1290-0729(00)00220-9

F. [. Belforte, P. Dabbene, and . Gay, LPV approximation of distributed parameter systems in environmental modelling. Environmental Modelling and Software, pp.1063-1070, 2005.

G. [. Box and . Jenkins, Time series analysis forecasting and control, 1970.

K. [. Banks and . Kunisch, Estimation Techniques for Distributed Parameter Systems, 1992.
DOI : 10.1007/978-1-4612-3700-6

L. [. Bhagavan and . Nardizzi, Parameter identification in linear distributed parameter systems, IEEE Transactions on Automatic Control, vol.18, issue.6, pp.18677-679, 1973.
DOI : 10.1109/TAC.1973.1100433

]. H. Bre10 and . Brezis, Functional analysis, Sobolev spaces and partial differential equations, 2010.

]. J. Can84 and . Cannon, The one-dimensional heat equation, 1984.

]. T. Car39, . [. Carleman, S. A. Coca, and . Billings, Sur unprobì eme d'unicité pour les systèmes d'´ equations aux dérivées partiellesàpartiellesà deux variables indépendantes. Almqvist & Wiksell Identification of coupled map lattice models of complex spatio-temporal patterns, Physics Letters A, vol.287, pp.65-73, 1939.

S. [. Coca and . Billings, Identification of finite dimensional models of infinite dimensional dynamical systems, Automatica, vol.38, issue.11, pp.1851-1865, 2002.
DOI : 10.1016/S0005-1098(02)00099-7

S. [. Chochol, D. Chesne, and . Remond, An original differentiation tool for identification on continuous structures, Journal of Sound and Vibration, vol.332, issue.13, pp.3338-3350, 2013.
DOI : 10.1016/j.jsv.2013.01.022

URL : https://hal.archives-ouvertes.fr/hal-00807827

]. J. Cla87 and . Claes, Numerical Solution of Partial Differential Equations by the Finite Element Method, 1987.

K. [. Curtain and . Morris, Transfer functions of distributed parameter systems: A tutorial, Automatica, vol.45, issue.5, pp.1101-1116, 2009.
DOI : 10.1016/j.automatica.2009.01.008

P. [. Crank and . Nicolson, A practical method for numerical evaluation of solutions of partial differential equations of the heat-conduction type, Mathematical Proceedings of the Cambridge Philosophical Society, vol.42, issue.01, pp.50-67, 1947.
DOI : 10.1098/rsta.1927.0008

N. [. Ciss, C. Parisey, J. Dedryver, and . Pierre, Understanding flying insect dispersion: Multiscale analyses of fragmented landscapes, Ecological Informatics, vol.14, 2013.
DOI : 10.1016/j.ecoinf.2012.11.004

URL : https://hal.archives-ouvertes.fr/hal-00818381

M. [. Chou, R. Verhaegen, and . Johansson, Continuous-time identification of SISO systems using Laguerre functions, IEEE Transactions on Signal Processing, vol.47, issue.2, pp.349-362, 1999.
DOI : 10.1109/78.740121

H. [. Curtain and . Zwart, An Introduction to Infinite-Dimensional Linear Systems Theory, Mathematics Subject Classifications, vol.21, 1991.
DOI : 10.1007/978-1-4612-4224-6

Y. [. Ding, T. Shi, and . Chen, Auxiliary model-based least-squares identification methods for Hammerstein output-error systems, Systems & Control Letters, vol.56, issue.5, pp.4015-4020, 2011.
DOI : 10.1016/j.sysconle.2006.10.026

J. Durbin, Errors in variables. Review of the international statistical institute, pp.23-32, 1954.

]. P. Eyk74 and . Eykhoff, System identification -Parameter and state estimation, 1974.

J. [. Fang, E. Wang, Z. Feng, and . Li, Parameter identification and application of a distributed parameter coupled system with a movable inner boundary, Computers & Mathematics with Applications, vol.62, issue.11, pp.4015-4020, 2011.
DOI : 10.1016/j.camwa.2011.09.035

S. [. Guo and . Billings, Identification of Partial Differential Equation Models for Continuous Spatio-Temporal Dynamical Systems, IEEE Transactions on Circuits and Systems II: Express Briefs, vol.53, issue.8, pp.657-661, 2006.
DOI : 10.1109/TCSII.2006.876464

S. [. Guo and . Billings, Identification and analysis of spatio-temporal dynamical systems using wavelets, International Journal of Systems Science, vol.166, issue.3, pp.315-334, 2008.
DOI : 10.1103/PhysRevLett.78.4297

]. M. Ggdh04, H. Gilson, P. Garnier, and . Van-den-hof, Instrumental variable methods for continuous-time model identification in closed-loop, American Control Conference, 2004.

M. [. Garnier, E. Gilson, and . Huselsein, Developments for the Matlab CONTSID toolbox, 13th IFAC Symposium on System Identification (SYSID'2003), pp.1007-1012, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00109102

M. [. Garnier, V. Gilson, and . Laurain, The CONTSID toolbox for Matlab: extensions and latest developments, 15th IFAC Symposium on System Identification, 2009.
DOI : 10.3182/20090706-3-FR-2004.00122

URL : https://hal.archives-ouvertes.fr/hal-00406485

M. [. Garnier, A. Gilson, and . Richard, CONTSID : a Matlab toolbox for direct continuous-time model identification from sampled data, Angers, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00085571

M. Gilson, H. Garnier, P. C. Young, and P. Van-den-hof, Instrumental variable methods for closed-loop continuous-time model identification. Identification of continuous-time models from sampled data, pp.133-160, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00161985

B. [. Gel-'fand and . Levitan, On the determination of a differential equation from its spectral function, Amer. Math. Soc. Transl, vol.1, pp.253-304, 1955.

M. [. Garnier and . Mensler, CONTSID : a continuous-time system identification toolbox for Matlab, 5th European Control Conference (ECC'99), 1999.

M. [. Garnier and . Mensler, The CONTSID toolbox : a Matlab toolbox for CONtinuous-Time System IDentification, 12th IFAC Symposium on System Identification (SYSID'2000), 2000.

J. Guilloux, T. Toilliez, T. Devillard, and P. Battaglia, Modélisation du transfert d'un polluant conservatif dans un ruisseau périurbain : comparaisons et mises en oeuvre de différents modèles, 2010.

M. Gilson and P. Van-den-hof, Instrumental variable methods for closed-loop system identification, Automatica, vol.41, issue.2, pp.241-249, 2005.
DOI : 10.1016/j.automatica.2004.09.016

URL : https://hal.archives-ouvertes.fr/hal-00089684

L. [. Garnier, P. C. Wang, and . Young, Identification of continuous-time models from sampled data, chapter Direct identification of continuous-time models from sampled data : issues, basic solutions and relevance, pp.1-30, 2008.

P. [. Garnier and . Young, What does continuous-time model identification have to offer?, 16th IFAC Symposium on System Identification, pp.810-815
DOI : 10.3182/20120711-3-BE-2027.00233

URL : https://hal.archives-ouvertes.fr/hal-00751733

P. [. Garnier and . Young, The advantages of directly identifying continuous-time transfer function models, special issue on Applications of Continuous-Time Model Identification and Estimation, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00996639

]. J. Had23 and . Hadamard, lectures on Cauchy's problems in linear partial differential equations, 1923.

H. [. Huselstein, A. Garnier, P. C. Richard, and . Young, La bo??tèbo??tè a outils CONTSID d'identification de modèlesmodèlesà temps continu -Extensions récentes, Conférence Internationale Francophone d'Automatique (CIFA'2002), pp.8-10, 2002.

I. [. Hamdi and . Mahfoudhi, Inverse source problem in a one-dimensional evolution linear transport equation with spatially varying coefficients: application to surface water pollution, Inverse Problems in Science and Engineering, vol.8, issue.6, 2013.
DOI : 10.1090/S0025-5718-1992-1106979-0

A. [. Hidayat, R. Núñez, B. Babu?, and . Schutter, Identification of distributedparameter systems with missing data, IEEE International Conference on Control Applications, Part of 2012 IEEE Multi-Conference on Systems and Control, pp.1014-1019, 2012.

C. [. Henrot, D. Soussen, and . Brie, Fast Positive Deconvolution of Hyperspectral Images, IEEE Transactions on Image Processing, vol.22, issue.2, pp.828-833, 2013.
DOI : 10.1109/TIP.2012.2216280

URL : https://hal.archives-ouvertes.fr/hal-00730503

S. [. Isakov, . Kindermannjoh94-]-r, and . Johansson, Identification of the diffusion coefficient in a onedimensional parabolic equation Inverse problems Identification of continuous-time models, Isakov. Inverse source problems, pp.665-680887, 1990.

. Kgm-+-11-]-m, S. Karalashvili, W. Grob, A. Marquardt, A. Mhandi et al., Identification of transport coefficient models in convection-diffusion equations Distributed parameter system identification-A survey, Klibanov. Inverse problems and carleman estimates. Inverse problemsLau10] V. Laurain. ContributionsàContributionsà l'identification de modèles paramétriques non linéaires, pp.303-327575, 1977.

]. R. Lev02 and . Leveque, ApplicationàApplicationà la modélisation de bassins versants ruraux UFR-Faculté des sciences et technologies Ecole Doctorale IAEM Lorraine, Octobre 2010 Finite volume methods for hyperbolic problems, 2002.

V. Laurain, M. Gilson, H. Garnier, and P. C. Young, Refined instrumental variable methods for identification of Hammerstein continuous-time Box-Jenkins models, 2008 47th IEEE Conference on Decision and Control, 2008.
DOI : 10.1109/CDC.2008.4738853

URL : https://hal.archives-ouvertes.fr/hal-00334463

V. Laurain, M. Gilson, R. Tóth, H. Garnier-[-lk01-]-y, Y. Li et al., Grey-box Identification of Distributed Parameter Systems Theory for the user Upper Saddle River Periodic solutions of periodic delay lotka?volterra equations and systems Modeling of distributed parameter systems for applications-A synthesized review from time-space separation Spatio-Temporal Modeling of Nonlinear Distributer Parameter Systems, volume 50 of Intelligent Systems, Control and Automation : Science and Engineering Direct identification of continuoustime linear parameter-varying input/output models Iterative least-squares parameter estimation for arma pulse response and output disturbance, Lju99] L. Ljung. System Identification, pp.959-967260, 1982.

R. Malti, M. Aoun, J. Sabatier, and A. Oustaloup, TUTORIAL ON SYSTEM IDENTIFICATION USING FRACTIONAL DIFFERENTIATION MODELS, 14th IFAC Symposium on System Identification, pp.606-611, 2006.
DOI : 10.3182/20060329-3-AU-2901.00093

URL : https://hal.archives-ouvertes.fr/hal-00180699

]. D. May67 and . Mayne, A method for estimating discrete-time transfer functions Regularisation aspects in continuous-time model identification, Advances in Computer Control, Second UKAC Control Convention, pp.197-208, 1967.

N. [. Moura, M. Chaturvedi, and . Krsti´ckrsti´c, PDE estimation techniques for advanced battery management systems — Part I: SOC estimation, 2012 American Control Conference (ACC), pp.559-565, 2012.
DOI : 10.1109/ACC.2012.6315019

H. [. Musha and . Higuchi, Traffic Current Fluctuation and the Burgers Equation, Japanese Journal of Applied Physics, vol.17, issue.5, pp.811-816, 1978.
DOI : 10.1143/JJAP.17.811

D. [. Morton and . Mayers, Numerical Solution of Partial Differential Equations, 2005.

S. [. Malti, O. Victor, A. Nicolas, and . Oustaloup, System Identification Using Fractional Models: State of the Art, Volume 5: 6th International Conference on Multibody Systems, Nonlinear Dynamics, and Control, Parts A, B, and C, pp.1-10, 2007.
DOI : 10.1115/DETC2007-35332

URL : https://hal.archives-ouvertes.fr/hal-00182374

W. [. Martinez and . Wise, Analysis of constructed treatment wetland hydraulics with the transient storage model OTIS, Nak93] S. Nakagiri. Reviw of japanese work of the last ten years on identifiabilty in distributed parameter systems. Inverse problems, pp.211-222143, 1993.
DOI : 10.1016/S0925-8574(03)00029-6

]. B. Øks03 and . Øksendal, Stochastic differential equations [Per09] A. Perasso. Identifiabilté de paramètres pour des systèmes décrits par deséquationsdeséquations aux dérivées partielles. ApplicationàApplicationà la dynamique des populations, 2003.

. Pqe-+-05-]-v, J. Puig, T. Quevedo, P. Escobet, E. Charbonnaud et al., Identification and control of an open-flow canal using LPV models, Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, pp.1893-1898, 2005.

J. [. Pintelon, Y. Schoukens, and . Rolain, Box???Jenkins continuous-time modeling, Automatica, vol.36, issue.7, pp.983-991, 2000.
DOI : 10.1016/S0005-1098(00)00002-9

]. L. Pyb-+-99, P. C. Price, D. Young, K. Berckmans, J. Janssens et al., Data-based mechanistic modelling and control of mass and energy transfer in agricultural buildings, Annual reviews in Control, vol.23, pp.71-82, 1999.

H. [. Söderström, B. Fan, S. Carlsson, and . Bigi, Least squares parameter estimation of continuous-time ARX models from discrete-time data, IEEE Transactions on Automatic Control, vol.42, issue.5, pp.659-673, 1997.
DOI : 10.1109/9.580871

H. [. Schorsch, M. Garnier, and . Gilson, Instrumental variable methods for identifying partial differential equation models of distributed parameter systems, IFAC Symposium on System Identification, pp.840-845
DOI : 10.3182/20120711-3-BE-2027.00421

URL : https://hal.archives-ouvertes.fr/hal-00761659

H. [. Schorsch, M. Garnier, P. C. Gilson, and . Young, Instrumental variable methods for identifying partial differential equation models, International Journal of Control, vol.16, issue.12, 2013.
DOI : 10.1080/00207178008961080

URL : https://hal.archives-ouvertes.fr/hal-00869215

M. [. Schorsch, V. Gilson, H. Laurain, and . Garnier, Identification of LPV partial differential equation models, 52nd IEEE Conference on Decision and Control, 2013.
DOI : 10.1109/CDC.2013.6760590

URL : https://hal.archives-ouvertes.fr/hal-00861956

L. [. Steiglitz and . Mcbride, A technique for the identification of linear systems, IEEE Transactions on Automatic Control, vol.10, issue.4, pp.461-464, 1965.
DOI : 10.1109/TAC.1965.1098181

R. [. Schoukens and . Pintelon, Identification of linear systems. A practical guideline to accurate modeling, 1991.

P. [. Söderström and . Stoica, Instrumental Variable Methods for System Identification, 1983.
DOI : 10.1007/BFb0009019

]. M. Ssk08a, M. Sadabadi, M. Shafiee, and . Karrari, Parameter estimation of two-dimensional linear differential systems via Fourier based modulation function, World IFAC Congress, vol.17, issue.1, pp.14385-14390, 2008.

]. M. Ssk08b, M. Sadabadi, M. Shafiee, and . Karrari, System identification of two-dimensional continuous-time systems using wavelets as modulating functions, ISA Transactions, vol.47, pp.256-266, 2008.

Z. [. Sagara, K. Yang, and . Wada, Parameter identification of distributed parameter systems in the presence of measurement noise, International Journal of Systems Science, vol.19, issue.8, pp.1391-1401, 1991.
DOI : 10.1016/0005-1098(81)90087-X

Z. [. Sagara and . Zhao, IDENTIFICATION OF SYSTEM PARAMETERS IN DISTRIBUTED PARAMETER SYSTEMS, World IFAC congress, p.3, 1990.
DOI : 10.1016/B978-0-08-041263-4.50081-6

Z. [. Sagara, K. Zhao, and . Wada, Parameter estimation of distributed-parameter systems under noisy measurements, Systems Science, vol.16, issue.4, pp.57-70, 1990.

M. [. Thil, H. Gilson, and . Garnier, On some instrumental variable-based methods for errors-in-variables model identification, 17th Triennial World IFAC Congress on Automatic Control, 2008.

]. R. Thdh12, P. S. Tóth, P. M. Heuberger, and . Van-den-hof, Prediction error identification of LPV systems : present and beyond, Control of Linear Parameter Varying Systems with Applications, pp.27-60, 2012.

]. E. Thi05 and . Thiébaut, Introduction to image reconstruction and inverse problems, Proceedings of the NATO Advanced Study Institute on Optics in Astrophysics, 2005.

V. [. Tóth, W. Laurain, K. Zheng, and . Poolla, Model structure learning: A support vector machine approach for LPV linear-regression models, IEEE Conference on Decision and Control and European Control Conference, pp.3192-3197, 2010.
DOI : 10.1109/CDC.2011.6160564

P. [. Tych and . Young, A Matlab software framework for dynamic model emulation . Environmental Modelling and Software, pp.19-29, 2012.

P. [. Taylor, A. A. Young, J. Chotai, and . Whittaker, Nonminimal state space approach to multivariable ramp metering control of motorway bottlenecks, Proceedings of the Institution of Electrical Engineers, pp.568-574, 1998.
DOI : 10.1049/ip-cta:19982383

]. S. Tza78 and . Tzafestas, Walsh series approach to lumped and distributed system identification, Journal of the Franklin Institute, vol.305, issue.4, pp.199-220, 1978.

N. [. Vaughan and . Mcintyre, An assessment of DBM flood forecasting models, Proceedings of the ICE -Water Management, pp.105-120, 2012.
DOI : 10.1680/wama.2012.165.2.105

]. J. Wal86 and . Walsh, An introduction to stochastic partial differential equations, 1986.

P. [. Wallis, K. J. Young, and . Beven, Experimental investigation of the aggregated dead zone model for longitudinal solute transport in stream channels, Proc. Inst. of Civil Engrs, vol.87, issue.2, pp.1-22, 1989.

H. [. Young, M. Garnier, and . Gilson, Identification of continuous-time models from sampled data, chapter Refined instrumental variable identification of continuous-time hybrid Box-Jenkins models, pp.91-132, 2008.

A. [. Young and . Jakeman, Refined instrumental variable methods of recursive time-series analysis Part III. Extensions, Theory of Self Adaptive Control Systems, pp.741-764, 1966.
DOI : 10.1080/00207178008961080

]. P. You69 and . Young, Applying parameter estimation to dynamic systems : Part II -applications, Control Engineering, vol.16, issue.11, pp.118-124, 1969.

]. P. You70 and . Young, An instrumental variable method for real-time identification of a noisy process, Automatica, vol.6, pp.271-287, 1970.

]. P. You76 and . Young, Some observations on instrumental variable methods of time-series analysis, International Journal of Control, vol.23, pp.593-612, 1976.

]. P. You84 and . Young, Recursive estimation and time-series analysis, 1984.

]. P. You11 and . Young, Recursive Estimation and Time-series Analysis : An Introduction for the Student and Practitioner, 2011.