2005
DOI: 10.1007/s00449-005-0409-1
|View full text |Cite
|
Sign up to set email alerts
|

Hybrid bounded error observers for uncertain bioreactor models

Abstract: 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… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

0
18
0
5

Year Published

2006
2006
2017
2017

Publication Types

Select...
6
1
1

Relationship

0
8

Authors

Journals

citations
Cited by 28 publications
(23 citation statements)
references
References 7 publications
0
18
0
5
Order By: Relevance
“…In response to this, some authors have proposed a way of combining the convergence and filtering advantages of the high gain approach together with the robustness of the asymptotic observers. For such observers, the state estimates first reach a neighborhood of the unmeasured states very rapidly, from which neighborhood the estimates then converge more slowly, but also more accurately, towards the true values of the state variables [13,14].…”
Section: Introductionmentioning
confidence: 99%
“…In response to this, some authors have proposed a way of combining the convergence and filtering advantages of the high gain approach together with the robustness of the asymptotic observers. For such observers, the state estimates first reach a neighborhood of the unmeasured states very rapidly, from which neighborhood the estimates then converge more slowly, but also more accurately, towards the true values of the state variables [13,14].…”
Section: Introductionmentioning
confidence: 99%
“…This observer gives good estimations but the interval selection and estimation convergence need to be improved. Other approaches have been tested as shown in Deza, Bossanne, Busvelle, Gauthier, and Rakotopara (1993), Alcaraz-Gonzalez et al (1999), Lemesle and Gouze (2005) and Chachuat and Bernard (2005). All these observers propose particular solutions; however, some disadvantages are noted, such as difficulties to design, tune and implementation, and numerical instability due to ill conditioning of the process dynamics, estimation errors due to model uncertainties, etc.…”
Section: Introductionmentioning
confidence: 95%
“…To tackle this drawback, new observer designs have been proposed recently in order to improve the estimation performance. In [7], an interval observer is designed based on a change of coordinates that involves a time-varying gain [15] which can be used to optimize the convergence rate of the estimation error. Nevertheless, this observer requires the gain derivative whose computation can be delicate (e.g.…”
Section: Introductionmentioning
confidence: 99%