DocumentCode :
2939172
Title :
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
Link To Document :
بازگشت