C04 - Numerical optimization methods for the identification and control of fluctuating systems
Funding period: 2021 – 2024
Project leaders: Stefan Volkwein (Gabriele Ciaramella until 03/2021)
Scientific staff: Jan Bartsch, Simon Buchwald, Gabriele Ciaramella (collaborator)
This project is concerned with the development of new efficient and robust numerical optimization methods that are capable of identifying nonlinear potentials, coupling terms, and kernels characterizing the evolution of fluctuating systems in presence of strong external driving forces. Particular focus will be put on non-linear resonators and barrier-crossing phenomena governed by the generalized Langevin equation. The numerical strategies that will be developed in this project aim at the calculation of optimized external driving forces that permits to produce experimental data that improves the identifiability of the sought nonlinear potentials, couplings and kernel functions.
List of publications
Current preprints
- Reconstruction of unknown nonlinear operators in semilinear elliptic models using optimal inputs
J. Bartsch, S. Buchwald, G. Ciaramella, S. Volkwein
arXiv:2405.12153 - published 20 May 2024
- Adjoint-based calibration of nonlinear stochastic differential equations
J. Bartsch, R. Denk, S. Volkwein
arXiv:2311.18422 - published 30 November 2023
2024
- Gauss–Newton Oriented Greedy Algorithms for the Reconstruction of Operators in Nonlinear Dynamics
S. Buchwald, G. Ciaramella, and J. Salomon
SIAM J. Control Optim., 62, 1343-1368 - published 3 May 2024
- A SPIRED code for the reconstruction of spin distribution
S. Buchwald, G. Ciaramella, J. Salomon and D. Sugny
Comput. Phys. Commun, 299, 109126 - published 15 February 2024
2021
- Greedy reconstruction algorithm for the identification of spin distribution
S. Buchwald, G. Ciaramella, J. Salomon, and D. Sugny
Phys. Rev. A, 104, 063112 – published 13 December 2021
- Analysis of a Greedy Reconstruction Algorithm
S. Buchwald, G. Ciaramella, and J. Salomon
SIAM Journal on Control and Optimization, 59, 4511 – published 29 November 2021
Further Publications
- Optimal Design of Experiments for a Lithium-Ion Cell: Parameters Identification of an Isothermal Single Particle Model with Electrolyte Dynamics
A. Pozzi, G. Ciaramella, S. Volkwein, and D. M. Raimondo
Ind. Eng. Chem. Res. 2019, 58, 3, 1286 - published 26 December 2018
- Formulation and Numerical Solution of Quantum Control Problems
A. Borzì, G. Ciaramella, and M. Sprengel
SIAM 2017
- Investigation of Optimal Control Problems Governed by a Time-Dependent Kohn-Sham Model
M. Sprengel, G. Ciaramella, and A. Borzì
J. Dyn. Control. Syst. 24, 657 - published 9 January 2018
- Admittance Identification from Point-wise Sound Pressure Measurements Using Reduced-order Modelling
S. Volkwein
J. Optim. Theory. Appl. 147, 169 - published 6 May 2010
- Parameter identification for nonlinear elliptic-parabolic systems with application in lithium-ion battery modeling
O. Lass, and Stefan Volkwein
Comput. Optim. Appl. 62, 217 - published 28 February 2015
- Newton Methods for the Optimal Control of Closed Quantum Spin Systems
G. Ciaramella, A. Borzì, G. Dirr, and D. Wachsmuth
SIAM J. Sci. Comput. 37, A319 - published 3 February 2015
- POD‐Galerkin approximations in PDE‐constrained optimization
E. W. Sachs, and S. Volkwein
GAMM-Mitteilungen 33, 194 - published October 2010