Simultaneous States and Parameters Estimation of an Ozonation Reactor Based on Dynamic Neural Network
نویسنده
چکیده
This paper deals with the simultaneous states and parameters estimation of an ozonation reactor using a dynamic neural network and the least squares method. We use a dynamic model derived from mass balance considerations. We propose a continuous time algorithm which includes two parallel procedures: state estimation using a Dynamic Neural Network (DNN) and parameters identification based on Least Squares Method (LSM). A set of numerical simulations has been carried out in order to illustrate the performance of this algorithm.
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