Interval observers for biochemical processes with uncertain kinetics and inputs

Rapaport, Alain; Dochain, Denis

doi:10.1016/j.mbs.2004.07.004

Cited by 82 publications

(107 citation statements)

References 18 publications

Supporting

Mentioning

107

Contrasting

Order By: Relevance

“…This assumption implies that, given a stabilization objective, it must be satisfied for any system too. This idea has been complemented with a worst case approach (see [7], [8], [17], [19], [20]) by using the fact that (under some transformation of variables) a system Σ (e.g. bioreactor equations) can be studied using monotone dynamical systems theory [23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust control for an uncertain chemostat model

Gouzé¹,

Robledo²

2005

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Using these systems (Σ − , Σ + ), interval observers for uncertain bioreactor models have been developed in [7], [8], [19], [20], allowing a partial estimation for the nonmeasured variables. Moreover, in [20] a feedback stabilization law is built using these interval observers.…”

Section: Introductionmentioning

confidence: 99%

Robust control for an uncertain chemostat model

Gouzé¹,

Robledo²

2005

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…The structures of interval observers can be found in (Gouzé et al, 2000;Alcaraz-González et al, 2004;Rapaport and Dochain, 2005). In (Alcaraz-González et al, 2004), it was shown that, if some conditions are satisfied by the system (24), then the interval observer for this system is stable and robust in spite of the uncertainty in the non-linear part of the system dynamics, inputs and initial conditions.…”

Section: Interval Observermentioning

confidence: 99%

“…Nevertheless, the linear part of the system dynamics represented by the state matrix A(t) is known and bounded A − ≤ A(t) ≤ A + , and there is no noise in the state measurements. Moreover, in (Rapaport and Dochain, 2005) it was shown that if state measurements are uncertain, the interval observer can still be stable. An application of the interval observer to the wastewater treatment process can be found in (Gouzé et al, 2000;Hadj-Sadok and Gouzé, 2001;Harmand and Rapaport, 2002;Alcaraz-González et al, 2004).…”

Section: Interval Observermentioning

confidence: 99%

Monitoring of Chlorine Concentration in Drinking Water Distribution Systems Using an Interval Estimator

Łangowski¹,

Brdyś²

2007

International Journal of Applied Mathematics and Computer Science

View full text Add to dashboard Cite

This paper describes the design of an interval observer for the estimation of unmeasured quality state variables in drinking water distribution systems. The estimator utilizes a set bounded model of uncertainty to produce robust interval bounds on the estimated state variables of the water quality. The bounds are generated by solving two differential equations. Hence the numerical efficiency is sufficient for on-line monitoring of the water quality. The observer is applied to an exemplary water network and its performance is validated by simulations.

show abstract

“…It becomes, a popular successful robust approach especially in biotechnological domain (Rapaport and Dochain (2005), Meslem et al (2008)). Note that, interval observers can be defined as a pair of estimators based on Luenberger structure which provide a guaranteed bounds covering all admissible trajectories of system, using a priori known bounds on uncertain parameters and/or exogenous disturbances.…”

Section: Introductionmentioning

confidence: 99%

Interval observer for LPV systems: Application to vehicle lateral dynamics

et al. 2017

View full text Add to dashboard Cite

This paper presents a new method for guaranteed and robust estimation of sideslip angle and lateral tire forces with consideration of cornering stiffness variations resulting from changes in tire/road and driving conditions. An interval LPV observer with both measurable and unmeasurable time-varying parameters is proposed. The longitudinal velocity is treated as the online measured time-varying parameter and the cornering stiffness at front and rear tires are assumed to be unknown but bounded with a priori known bounds. The obtained results are no more punctual values but a set of acceptable values. The simulation is based on experimental data in order to prove the effectiveness of the proposed observers.

show abstract

Interval observers for biochemical processes with uncertain kinetics and inputs

Cited by 82 publications

References 18 publications

Robust control for an uncertain chemostat model

Robust control for an uncertain chemostat model

Monitoring of Chlorine Concentration in Drinking Water Distribution Systems Using an Interval Estimator

Interval observer for LPV systems: Application to vehicle lateral dynamics

Contact Info

Product

Resources

About