System identification: theory for the user
System identification: theory for the user
Piecewise polynomial nonlinear model reduction
Proceedings of the 40th annual Design Automation Conference
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This paper describes a novel approach to the problem of model order reduction (MOR) of very large nonlinear systems. We consider the behavior of a dynamic nonlinear system as having two fundamental characteristics: a global behavioral "envelope" that describes major transformations to the state of the system under external stimuli and a local behavior that describes small perturbation responses. The nonlinear low order envelope function is generated by using the remainders from the coalescence of projection bases taken through a space-state sample. A behavioral model can then be expressed as the superposition of these two descriptions, operating according to the input stimuli and the current state value.