Parameter and state estimation of the activated sludge process—I. Model development

• Published in: Water research (Oxford) Vol. 30; no. 12; pp. 2853 - 2865
• Main Authors: Kabouris, John C., Georgakakos, Aris P.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 1996; Elsevier Science
• Subjects: activated sludge; Applied sciences; Biological and medical sciences; Biological treatment of waters; Biotechnology; Environment and pollution; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General purification processes; IAWPRC Activated Sludge Model 1; Industrial applications and implications. Economical aspects; parameter and state estimation; Pollution; process measurements; stochastic process modeling; Wastewaters; Water treatment and pollution; IAWPRC Activated Sludge Model 1; parameter and state estimation; stochastic process modeling; activated sludge; process measurements; Activated sludge; Stochastic analysis; Waste water purification; Modeling; Biological purification
• ISSN: 0043-1354; 1879-2448
• DOI: 10.1016/0043-1354(95)00325-8

A new approach is introduced for combined state and parameter estimation, named Linearized Maximum Likelihood (LML). The LML method is motivated by the uncertain and nonlinear activated sludge dynamics. In this article, the theoretical background leading to the development of the LML method is presented, along with the resulting numerical algorithm. In a companion article (Kabouris and Georgakakos, 1996) the LML method is applied to the parameter and state estimation of a nitrifying activated sludge process, modelled by the IAWPRC Activated Sludge Model 1.