Comparisons of nonlinear estimators for wastewater treatment plants

Author

Wahab, H.F. ; Katebi, R. ; Villanova, R.

Author_Institution

Dept. of Electr. & Electron. Eng., Univ. of Strathclyde, Glasgow, UK

fYear

2012

fDate

3-6 July 2012

Firstpage

764

Lastpage

769

Abstract

This paper deals with five existing nonlinear estimators (filters), which include Extended Kalman Filter (EKF), Extended H-infinity Filter (EHF), State Dependent Filter (SDF), State Dependent H-Infinity Filter (SDHF) and Unscented Kalman Filter (UKF) that are formulated and implemented to estimate unmeasured states of a typical biological wastewater system. The performance of these five estimators of different complexities, behaviour and advantages are demonstrated and compared via nonlinear simulations. This study shows promising application of UKF for monitoring and control of the process variables, which are not directly measurable.

Keywords

H_∞ filters; Kalman filters; filtering theory; industrial plants; nonlinear estimation; nonlinear filters; state estimation; wastewater treatment; biological wastewater system; biological wastewater treatment plants; extended H-infinity filter; extended Kalman filter; nonlinear estimators; nonlinear simulations; process variable control; process variable monitoring; state dependent H-Infinity filter; state dependent filter; unmeasured state estimation; unscented Kalman filter; Approximation algorithms; Biological system modeling; Biomass; Filtering algorithms; H infinity control; Kalman filters; Noise measurement; H-infinity filter; Kalman filter; Nonlinear state estimation; Unscented Kalman filter; Wastewater Systems; state-dependent filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation (MED), 2012 20th Mediterranean Conference on

Conference_Location

Barcelona

Print_ISBN

978-1-4673-2530-1

Electronic_ISBN

978-1-4673-2529-5

Type

conf

DOI

10.1109/MED.2012.6265730

Filename

6265730