FREQUENCY-DOMAIN STRUCTURAL SYSTEM, IDENTIFICATION BY OBSERVABILITY RANGE SPACE EXTRACTION

This paper presents the Frequency Domain Observability Range Space Ext raction (FORSE) identification algorithm. FORSE is a singular value de composition based identification algorithm which constructs a state sp ace model directly from frequency domain data. The concept of system i dentification by observability range space extraction was developed by generalizing the Q-Markov Covariance Equivalent Realization and Eigen system Realization Algorithm. The numerical properties of FORSE are we ll behaved when applied to multi-variable and high dimensional structu ral systems. It can achieve high modeling accuracy by properly overpar ameterizing the system. The effectiveness of this algorithm for struct ural system identification is demonstrated using the MIT Middeck Activ e Control Experiment (MACE). MACE is an active structural control expe riment to be conducted in the Space Shuttle middeck. Results of ground experiments using this algorithm will be discussed.