Abstract
This paper presents the frequency domain observability range space extraction (FORSE) identification algorithm. FORSE is a singular value decomposition based identification algorithm which constructs a state space model directly from frequency domain data. It is numerically well behaved when applied to multivariable and high dimensional structural systems. It can achieve high modeling accuracy by properly overparametering the model. Its effectiveness for structural systems is demonstrated using the MIT Middeck Active Control Experiment (MACE). MACE is an active structural control experiment to be conducted in the Space Shuttle middeck.
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