Impact of NNs accuracy on FB/FF pH neutralization control system performance

This paper studies the impact of neural network accuracy on the feedback/feed-forward (FB/FF) pH neutralization control system performance. Five neural networks (NNs) are incorporated in a FB/FF control structure in order to perform nonlinear compensation of the non-measurable input disturbances. Two significant problems connected with the application of the FF scheme are discussed - the appearance of oscillations and the offset of the system output from its desired value. A procedure for adding of auxiliary points in the training data set when the NNs accuracy is not sufficient is derived. Simulation results are presented.