MODEL UPDATING OF LINEAR-SYSTEMS BY SELECTIVE SENSITIVITY WITH DELIBERATE STRUCTURAL MODIFICATION

We extend the model-updating method of selective sensitivity by employ ing deliberate structural modifications. The resulting system-identifi cation procedure reduces ambiguities in model-updating in two ways: by augmenting the data base of the identification and by reducing the di mensionality of the individual parameter estimations. It is shown that deliberate structural modification allows selectively sensitive excit ations with fewer actuators than in ordinary selective sensitivity. Th e theory for choosing the structural modifications and the selectively sensitive inputs is developed and illustrated with two examples. Forw ard multi-hypothesis estimation is illustrated. It is suggested that t he technology underlying smart programmable structures provides one me thod for implementing the ideas developed here.