Abstract
AbstractA number of strategies for state and parameter estimation for a centrifugal compressor system are investigated using a nonlinear dynamical model. It is found that high frequency measurements can be combined with lower frequency measurements to achieve high fidelity state estimation for stable equilibria, limit cycles, as well as transients using either a multirate discrete extended Kalman filter or a data fusion based algorithm with one independent estimator per measurement. When there is a change in one of the parameters of the system only a filter designed to adapt to such changes produces estimates with acceptable errors for a locally stable equilibrium.
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