Passivity of an identified model is crucial in simulation and prediction applications. This paper proposes a two-step procedure that generates guaranteed passive transfer function models from noisy data. It consists of an unconstrained optimal noise removal step, followed by passivity enforcement of the unconstrained model.
|Number of pages||7|
|Journal||IEEE Transactions on Instrumentation and Measurement|
|Publication status||Published - 1 Oct 2008|
- Constrained optimization
- passive models
- positive real functions
- system identification