State Estimation Using Microprocessors for Process Supervision and Control
Microprocessor-based state estimation in connection with process supervision and control is treated in this article. The state-of-the-art is briefly analysed on the basis of a literature survey, which confirms that very few on-line applications exist. The most commonly used state estimation algorithms, i.e. the Luenberger type observer, the Kalman-Bucy filter, the extended Kalman filter, as well as a nonlinear extension especially suitable for on-line computation, are reviewed with some comments concerning their applicibility to microprocessor-based process control. Applications concerning on-line state estimation of the activated sludge waste water treatment process and a pH control process are introduced.
KeywordsActivate Sludge State Estimation Extended Kalman Filter Nonlinear Filter State Estimation Problem
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