Predictive techniques based on neural networks are investigated in an adaptive structure for on-line control of a process exhibiting nonlinearities and typical disturbances. The method proposed consists of a novel identification technique based on additional memory adaptation and an efficient implementation of the predictive control, based on a nonlinear programming method. A forced circulation evaporator was chosen as a realistic nonlinear case study for the techniques discussed in the paper.
predictive control, nonlinear models, neural networks, on-line control.
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