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Computers & Chemical Engineering, Vol.23, No.S, S261-S264, 1999
A self tuning controller for multicomponent batch distillation with soft sensor inference based on a neural network
Multicomponent batch distillation is an operation difficult to control not only for its nonlinear and transient behaviour, but because the product quality cannot be measured rapidly and with reliability. In the present work, a computational system for direct digital control is developed for a pilot plant batch distillation column. The development of a self tuning regulator and a soft sensor of composition based on a neural network is described. Top and reboiler temperature measurements are the basis for the on-line composition inference. The computational system was experimentally tested in a computer operated pilot column. It could be seen that the neural network soft sensor is a feasible and a reliable tool to solve on-line operational problems of the control engineering systems. The developed control system permits to operate the batch distillation column efficiently and is easy to be implemented and operated.