| 摘要 |
For estimating a value of a vector of variables p in a mathematical model representing a physical process, where a state vector x of the model is estimated by a State Augmented Extended Kalman Filter (SAEKF), and where that the vector of variables p represents one or more properties of the process and is representable by a function of the state vector x, the following steps are executed: a) measuring values for measured variables u, b) incorporating the vector of variables p as an augmented state in the SAEKF, and c) computing an estimate of the complete state including the augmented state according to a SAEKF algorithm. That is, process properties themselves are estimated, and not polynomial coefficients for computing the variables from the state, as is usually done in the SAEKF.
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