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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/1247 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/1247 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/1247 archive 351 disk0/00/00/12/06 2016-01-15 01:47:04 2021-08-27 17:09:34 2016-01-15 01:47:04 monograph show 2 Beck M.B. 562 pub iis_wat iis_env iis_mod prog_ren Results from a small collaborative project on modeling and control of the activated sludge process are presented. The identification of a dynamic model for nitrification is discussed using time-series field data from the Norwich Sewage Works in eastern England. This analysis of the field data is also used for examination of the feasibility and benefits of on-line (or real-time) state estimation in the context of activated sludge process control. A recursive estimation algorithm -- the extended Kalman filter -- is applied both for system identification and state estimation. The results illustrate an unstable nitrification condition associated with a period in which new plant was being commissioned. It is found that both oxygen limitation of nitrification and the compaction of solids in the clarifier are important factors affecting process dynamics. For real-time operation of the process it is argued that models and forecasting algorithms may be best utilized as a support service for the plant management in their day-to-day decision-making role. 1979-07 published PP-79-003 PP-79-003 10 2986 public professional_paper IIASA, Laxenburg, Austria 47 FALSE info:eu-repo/semantics/book