Nonlinear predictive control using local models — applied to a batch fermentation process

• Published in: Control engineering practice Vol. 3; no. 3; pp. 389 - 396
• Main Authors: Foss, B.A., Johansen, T.A., Sørensen, A.V.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.1995
• Subjects: Fermentation processes; Identification; Nonlinear systems; Predicative control; Process Models; Identification; Fermentation processes; Nonlinear systems; Process Models; Predicative control
• ISSN: 0967-0661; 1873-6939
• DOI: 10.1016/0967-0661(95)00012-J

The problem of controlling processes that operate within a wide range of operating conditions is addressed. The operation of the process is decomposed into a set of operating regimes, and simple local state-space model structures are developed for each regime. These are combined into a global model structure using an interpolation method. Unknown local model parameters are identified using empirical data. The control problem is solved using a model predictive controller based on this model representation. As an example, a simulated batch fermentation reactor is studied. The model-based controller's performance is compared to the performance with an exact process model, and a linear model. It is experienced that a non-linear model with good prediction capabilities can be constructed using elementary and qualitative process knowledge combined with a sufficiently large amount of process data.