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State Estimation Using Microprocessors for Process Supervision and Control

  • Andrea Holmberg
  • Jussi Orava
Chapter
Part of the International Series on Microprocessor-Based Systems Engineering book series (ISCA, volume 1)

Abstract

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.

Keywords

Activate Sludge State Estimation Extended Kalman Filter Nonlinear Filter State Estimation Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© D. Reidel Publishing Company 1983

Authors and Affiliations

  • Andrea Holmberg
    • 1
  • Jussi Orava
    • 1
  1. 1.Systems Theory LaboratoryHelsinki University of TechnologyEspoo 15Finland

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