Abstract
Abstract On-line identification of the oxygen transfer rate, K L a, and the respiration rate in an activated sludge process is the topic of this paper. The nonlinear K L a function is modelled with a static, constrained, piecewise linear model, while the respiration rate is modelled as a random walk. A Kalman filter type recursive identification algorithm is applied in order to estimate the oxygen transfer rate and the respiration rate from measurements of dissolved oxygen concentration and air flow rate. The approach is illustrated using simulated and real data. A theoretical analysis is also performed where conditions for parameter identifiability are derived.
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