The parameter estimation algorithms based on the dynamical response measurement data

• Published in: Advances in mechanical engineering Vol. 9; no. 11; p. 168781401773000
• Main Author: Xu, Ling
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.11.2017; Sage Publications Ltd; SAGE Publishing
• Subjects: Accuracy; Algorithms; Computer simulation; Construction costs; Decomposition; Dynamical systems; Estimates; Experiments; Fault diagnosis; Innovations; Kalman filters; Laplace transforms; Methods; Neural networks; Parameter estimation; Parameter identification; Parameters; Process controls; Signal processing; rolling optimization; multi-innovation; Parameter estimation; system response; nonlinear optimization

This article studies the parameter estimation to the system response from the discrete measurement data. By constructing the dynamical rolling cost functions and using the nonlinear optimization, the gradient identification method is presented for estimating the parameters of the sine response signa...