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 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.