Abstract
This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.
Original language | English |
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Title of host publication | Proceedings of the 2000 American Control Conference, 2000 |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2740-2744 |
Volume | 4 |
ISBN (Print) | 0780355199 |
DOIs | |
Publication status | Published - 2000 |
Keywords
- Kalman filters, data reconciliation, differential algebraic equations, mixing process, nonlinear systems, process control, sequential modular simulators