Time Domain State Space Identification of Structural Systems

[+] Author and Article Information
Ketao Liu, David W. Miller

Space Engineering Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139

J. Dyn. Sys., Meas., Control 117(4), 608-618 (Dec 01, 1995) (11 pages) doi:10.1115/1.2801121 History: Received June 17, 1992; Revised August 22, 1994; Online December 03, 2007


An integrated time domain state space identification technique for structural systems is presented. This technique integrates the Observability Range Space Extraction identification algorithm, Balanced Realization model reduction algorithm, and Least Square model updating algorithm to generate low order and highly accurate state space models for structural systems based upon time domain data. The algorithms are integrated in such a manner that the Observability Range Space Extraction identification algorithm is used to generate an initial overparameterized state space model and then the Balanced Realization model reduction and Least Square model updating algorithms are used to iteratively reduce and update the model to achieve minimum prediction errors in time domain. We shall present the Observability Range Space Extraction identification algorithm and the Least Square model updating algorithm and discuss the integrated identification technique. The MIT Middeck Active Control Experiment (MACE) is used as an application example. MACE is an active structure control experiment to be conducted in the Space Shuttle middeck. Results of ground experiments using this technique will be discussed.

Copyright © 1995 by The American Society of Mechanical Engineers
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