Year: 2010
Type: article
Abstract: Data-based model refinement improves the fidelity of a model based on empirical observations.The model refinement structure is a closed-loop system consisting of an initial model, which is assumed to be known, and a feedback correction, which is unknown.We take advantage of the similarity between the feedback structure of model refinement and adaptive feedback control by replacing the unknown correction term with a retrospectivecost-based adaptive control law.The adaptive control law thus estimates the unknown subsystem.We investigate scenarios in which the initial model is derived from physical principles, such as mass-spring-damper systems, in order to obtain estimates of stiffness and damping coefficients.Furthermore, we identify dynamic subsystems for a linear initial model and a nonlinear initial model.
Institutions: Armstrong Flight Research Center, Data Fusion Research Center
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4298208999