Modelling of Wastewater Treatment Plant for Monitoring and Control Purposes by State – Space Wavelet Networks

Adam Borowa, Mietek A. Brdys, Krzysztof Mazur


Most of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - SpaceWavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of the wastewater treatment plant. The learning algorithms and basis function (multidimensional wavelets) are also proposed. The simulation results based on real data record are presented.


neural network models, model approximation, learning algorithms, waste treatment

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Copyright (c) 2017 Adam Borowa, Mietek A. Brdys, Krzysztof Mazur

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