Estimation of non-separable regressions containing parameter dependent exponential functions
This paper presents a method for generating a separable regression function from a nonseparable one, enabling theapplication of parameter estimation methods. In particular, we are interested in regressions containing parameter-dependent exponential functions - a scenario often encountered in physical systems. Our approach is based on algebraic techniques with the so-called annihilator theory, and utilizes an intermediate approximation of the nonlinear part by a polynomial function of the time. Two operators are proposed to define the annihilators: time delays and differential operators. The efficiency of the proposed approach is demonstrated in a nonlinearly parameterized fuel cell estimation problem.
Authors
- Roméo Ortega (ORCID: https://orcid.org/0000-0002-7747-5405)
- Denis V. Efimov (ORCID: https://orcid.org/0000-0001-8847-5235)
- Rosane Ushirobira (ORCID: https://orcid.org/0000-0001-9758-5743)
- José Guadalupe Romero (ORCID: https://orcid.org/0000-0002-9752-9095)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université de Lille (FR)
Publication Details
- Published
- 2024-12-16
- DOI
- https://doi.org/10.1109/cdc56724.2024.10886686
- Citations
- 1
- Primary Topic
- Advanced Statistical Methods and Models
- Type
- article
- Field-Weighted Citation Impact
- 0.71