Application of Neural Network based Control Strategies to Binary Distillation Column

作者：Singh Amit Kumar^*; Tyagi Barjeev; Kumar Vishal

来源：Control Engineering and Applied Informatics, 2013, 15(4): 47-57.

• Direct inverse control (DIC)
• feed forward networks (FFN)
• internal model control (IMC)
• model reference Adaptive control (MRAC)
• distillation column

This paper presents three different neural network based control schemes to the control of the Distillate composition of binary distillation column. The main goal is to control a single output variable, the Distillate composition, by changing two manipulated input variables, reflux flow rate and steam flow rate. A first-principle equation based model of binary distillation column is developed in SIMULINK (R) and validated by the experimental results. This model is used here as a reference model on which the developed neural control schemes have been applied. Three approaches Neural Network based Direct Inverse control (NN-DIC), Neural network based model reference adaptive control (NN-MRAC) and Neural network based internal model control (NN-IMC), are simulated and their performances are assessed. Comparison was also made with conventional PID cascade control. The results demonstrate that NN-IMC strategy provides a better performance than PID, NN-DIC and NN-MRAC for the cases analyzed.

• 出版日期2013-12