On-line robust nonlinear state estimators for nonlinear bioprocess systems

► A new robust nonlinear estimator for bioprocess nonlinear systems. ► State-dependent Riccati equation formulation and the technique of H-infinity control design are considered. ► The new filter is implemented and tested on a biological wastewater process. ► A complete numerical simulation study co...

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Bibliographic Details
Published in:Communications in nonlinear science & numerical simulation 2012-04, Vol.17 (4), p.1739-1752
Main Authors: Iratni, A., Katebi, R., Mostefai, M.
Format: Article
Language:English
Subjects:
ASM1
Computer simulation
Design engineering
Dynamical systems
Estimators
H-infinity
Mathematical models
Nonlinear dynamics
Nonlinear estimator
Nonlinearity
Simulation study
State-dependent Riccati equation
Waste water
Wastewater systems
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Summary:► A new robust nonlinear estimator for bioprocess nonlinear systems. ► State-dependent Riccati equation formulation and the technique of H-infinity control design are considered. ► The new filter is implemented and tested on a biological wastewater process. ► A complete numerical simulation study compares the EKE, SDRE, and the EHE with the new SDHE. ► The SDHE has superior performance and gives the most accurate state estimates. This paper presents the design of a new robust nonlinear estimator for estimation of states of nonlinear systems. Two approaches are considered based on the state-dependent Riccati equation formulation and the technique of H-infinity control design. The proposed method differs from other well-known state estimators, because not only nonlinear dynamics but also the robustness is taken into account. The proposed method is implemented and tested on a biological wastewater system. The simulation study compares the Extended Kalman Estimator ( EKE), the State-Dependent Riccati Estimator ( SDRE), and the Extended H-infinity Estimator ( EHE) with a new proposed State Dependent H-infinity Estimator ( SDHE). The results are compared for different weather conditions, i.e. dry, rain and storm, showing a superior performance of the proposed method.
ISSN:1007-5704
1878-7274
DOI:10.1016/j.cnsns.2011.09.032