The design of robust model predictive control for handling bounded uncertainties in step response of unconstrained MIMO processes is considered. The control law is obtained by minimizing an upper bound of the objective function and it consists of an optimal state feedback gain and a robust state obs
Robust control for an uncertain chemostat model
โ Scribed by Jean-Luc Gouze; Gonzalo Robledo
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 603 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1049-8923
- DOI
- 10.1002/rnc.1047
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โฆ Synopsis
Abstract
In this paper we consider a control problem for an uncertain chemostat model with a general growth function and cell mortality. This uncertainty affects the model (growth function) as well as the outputs (measurements of substrate). Despite this lack of information, an upper bound and a lower bound for those uncertainties are assumed to be known a priori. We build a family of feedback control laws on the dilution rate, giving a guaranteed estimation on the unmeasured variable (biomass), and stabilizing the two variables in a rectangular set, around a reference value of the substrate. We give two realistic applications of this control law to a depollution process and to phytoplankton culture. Copyright ยฉ 2005 John Wiley & Sons, Ltd.
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