Estimation of Activated Sludge Model Parameters Using Respirogram and Genetic Algorithms

A new parameter estimation method using respirogram and genetic algorithm (GA) to determine the activated sludge model is presented. Simplified respiration model based on ASM3 is used to verify the method. The model is composed of 5 wastewater components and 5 biological processes, which include 9 kinetic parameters. Synthetic data generated by respiration model is used to confirm estimation capability of proposed algorithm. GA adopts root mean square error (RMSE) between original parameter values and estimated values as the objective function. The results of applying this approach show that important kinetic parameters of activated sludge model can be estimated simultaneously using the proposed method. To confirm the applicability of the method, the measured respirogram using the influent of a domestic wastewater treatment plant is used to estimate the wastewater composition.