Hybrid bounded error observers for uncertain bioreactor models.
In this paper, we build bounded error observers for a common class of partially known bioreactor models. The main idea is to construct hybrid bounded observers "between" high gain observer, which has an adjustable convergence rate but requires perfect knowledge of the model, and asymptotic observer which is very robust towards uncertainty but has a fixed convergence rate. An hybrid bounded error observer which reconstructs the two state variables is constructed considering two steps: first step is similar to a high gain observer meaning that fast convergence rate but error depending on the knowledge of the model are obtained; second step is a switch to an observer similar to the asymptotic one meaning that fixed convergence rate towards an error as small as desired is obtained. Thus, a better convergence rate of estimated variables than the classical asymptotic observer is obtained.
Comore, Inria, BP 93, 06902 Sophia-Antipolis cedex, France. Valerie.Lemesle@sophia.inria.fr
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D000465:Algorithms; D018407:Bacterial Physiological Phenomena; D001426:Bacterial Proteins / Q000378:metabolism*; D001704:Biopolymers / Q000737:chemistry / Q000378:metabolism*; D019149:Bioreactors / Q000382:microbiology*; D018929:Cell Culture Techniques / Q000379:methods; D003198:Computer Simulation; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology; D007700:Kinetics; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D008956:Models, Chemical; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods
D001426:Bacterial Proteins; D001704:Biopolymers