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

✍ Scribed by B.A. Foss; T.A. Johansen; A.V. Sørensen

• Publisher: Elsevier Science
• Year: 1995
• Tongue: English
• Weight: 759 KB
• Volume: 3
• Category: Article
• ISSN: 0967-0661
• DOI: 10.1016/0967-0661(95)00012-j

✦ Synopsis

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 localstate-space model structures are developed for each regime. These are combined into a global model structure using an interpolation method. Unknown local model parameters axe 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.