Abstract
This paper describes a method for the state estimation of nonlinear systems described by a class of differential-algebraic equation models using the extended Kalman filter. The method involves the use of a time-varying linearisation of a semi-explicit index one differential-algebraic equation. The estimation technique consists of a simplified extended Kalman filter that is integrated with the differential-algebraic equation model. The paper describes a simulation study using a model of a batch chemical reactor. It also reports a study based on experimental data obtained from a mixing process, where the model of the system is solved using the sequential modular method and the estimation involves a bank of extended Kalman filters.
| Original language | English |
|---|---|
| Pages (from-to) | 267-281 |
| Journal | Control Engineering Practice |
| Volume | 9 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 2001 |
Keywords
- state estimation, generalised state space, large-scale systems, extended Kalman filters, process models, nonlinear systems, batch reactors
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