Input/output versus output-only data processing for structural identification—Application to in-flight data analysis

The problem of structural model identification under both known and unknown input excitations, is addressed. In-flight data analysis is an important instance of that problem. Input/output and output-only eigenstructure identification methods are described and compared, within two classes of methods: subspace-based and prediction error. In particular, different types of relevant projections for handling the known and unknown inputs are discussed. The relevance of the methods is emphasized through numerical results obtained on real flight test data sets.