A New Approach for Practical Identifiability Analysis Applied to Dynamic Phenomenological Models

摘要

Identifiability analysis is an essential tool for parameter estimation of dynamic models. The objective of this technique is to verify which parameters of this model should be identified. This paper proposes a new methodology, based in control system theory applied to the local sensitivity analysis of the model. First, the sensitivity matrix is scaled by applying an optimization problem that minimizes the condition number of the system. Then, analyzing the NSRGA matrix of the system, the most appropriated subset of parameters to be estimated is selected. To assess the proposed methodology, a case study is presented.