Observer Markov Parameter Identification Theory for Time Varying Eigensystem Realization Algorithm Conference Paper uri icon

abstract

  • This manuscript develops a theory for the Identification of Observer Markov Parameters for use with Time Varying Eigensystem Realization Algorithm. The theory thus developed turns out to be an extension of the celebrated Observer Kalman Filter Identification Method for Markov Parameter Estimation, proposed by Juang.1,2 The introduction of a time varying observer feedback within the Eigensystem Realization architecture aids in data compression and smoothing of the plant model histories. Numerical simulations demonstrate the effectiveness of the method. 2008 by Manoranjan Majji and John L. Junkins.

name of conference

  • AIAA Guidance, Navigation and Control Conference and Exhibit

published proceedings

  • AIAA Guidance, Navigation and Control Conference and Exhibit

author list (cited authors)

  • Majji, M., & Junkins, J.

citation count

  • 1

complete list of authors

  • Majji, Manoranjan||Junkins, John

publication date

  • August 2008