Title :
Impact of NNs accuracy on FB/FF pH neutralization control system performance
Author :
Galibova, Margarita ; Hadjiski, Mincho
Author_Institution :
Univ. of Chem. Technol. & Metall., Sofia, Bulgaria
Abstract :
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.
Keywords :
compensation; feedback; feedforward; learning (artificial intelligence); neurocontrollers; pH control; control system performance; feedback control; feedforward control; neural network accuracy; neural networks; nonlinear compensation; nonmeasurable input disturbances; oscillations; pH neutralization control; simulation; training data set; Adaptive control; Chemical industry; Chemical processes; Control nonlinearities; Control systems; Neural networks; Open loop systems; Pi control; Programmable control; System performance;
Conference_Titel :
Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium
Print_ISBN :
0-7803-7134-8
DOI :
10.1109/IS.2002.1042583
