On estimation of unknown state variables in wastewater systems

A. Iratni, M.R. Katebi, R. Vilanova, M. Mostefai

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

This paper focuses on the estimation of the non-measurable physical states of wastewater systems when nonlinear models with uncertainties describe the processes. The activated sludge process (ASP), as the most commonly applied biological wastewater purification technique, attracts a great deal of attention from the research community. We developed for this class of processes a state dependent differential Riccati filter (SDDRF) for state estimation of nonlinear model describing the system. The resulting software sensor is simple to implement and has a relatively low computational cost. The results are compared with the extended Kalman filter (EKF) in order to demonstrate the better performance of the SDDRF filter. The filter allows the on-line tracking of process variables, which are not directly measurable. The simulation results point out to the advantage of using this approach.
Original languageEnglish
Pages1-6
Number of pages6
DOIs
Publication statusPublished - Sep 2009
EventIEEE Conference on Emerging Technologies and Factory Automation, 2009 - Palma de Mallorca, Spain
Duration: 22 Sep 200925 Sep 2009

Conference

ConferenceIEEE Conference on Emerging Technologies and Factory Automation, 2009
CountrySpain
CityPalma de Mallorca
Period22/09/0925/09/09

Keywords

  • chemical sensors
  • nonlinear control systems
  • purification
  • sludge treatment
  • state estimation
  • wastewater treatment

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