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On-line robust nonlinear state estimators for nonlinear bioprocess systems
Authors:A Iratni  R KatebiM Mostefai
Institution:a Centre Universitaire de B.B. Arreridj, B.B. Arreridj 34265, Algeria
b Industrial Control Centre, Dept. of Electronic and Electrical Engineering, University of Strathclyde, 50 George Street, Glasgow G1 1QE, UK
c Laboratoire d’Automatique de Setif, Department of Electrical Engineering, University of Ferhat Abbas, 19000 Setif, Algeria
Abstract: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.
Keywords:Nonlinear estimator  Simulation study  Wastewater systems  ASM1  H-infinity  State-dependent Riccati equation
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