Observer Markov Parameter Identification Theory for Time Varying Eigensystem Realization Algorithm
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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.
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