title: Robust soft sensors for SBR monitoring.
abstract: In wastewater treatment some process variables may be very difficult to measure directly because of the non-availability or excessive cost of sensors. An alternative is to use "soft sensors" that provide online estimates of these inaccessible variables by calculations based on auxiliary measurable variables. Two such sensors are proposed based on extended Kalman filtering or neural networks that could enable the monitoring of nitrate ion, ammonium ion and carbonaceous matter concentrations during nitrification of wastewater.
authors.affiliation: COPPE-Federal University of Rio de Janeiro-Brazil.
authors.forename: D
authors.initials: D
authors.lastname: Zyngier
authors.forename: O Q
authors.initials: OQ
authors.lastname: Araújo
authors.forename: M A
authors.initials: MA
authors.lastname: Coelho
authors.forename: E L
authors.initials: EL
authors.lastname: Lima
mesh_terms: D019149:Bioreactors; D002244:Carbon / Q000032:analysis; D016571:Neural Networks, Computer; D009566:Nitrates / Q000032:analysis; D009584:Nitrogen / Q000302:isolation & purification; D000644:Quaternary Ammonium Compounds / Q000032:analysis; D014865:Waste Disposal, Fluid / Q000379:methods* / Q000706:statistics & numerical data
chemical_list: D009566:Nitrates; D000644:Quaternary Ammonium Compounds; D002244:Carbon; D009584:Nitrogen