Author(s)

Feng Li

.

Taking advantage of the knowledge of top and bottom compositions of a distillation column, a dynamic neural network (DNN) is designed to identify the input-output relationship of the column. The weight-training algorithm is derived from a Lyapunov function. Based on this empirical model, a nonlinear H_∞ controller is synthesized. The effectiveness of the control strategy is demonstrated using simulation results.

Distillation Column, Dynamic Neural Network, Nonlinear H_∞ Control

Li, F. (2011) Dynamic Neural Network Based Nonlinear Control of a Distillation Column. Intelligent Control and Automation, 2, 383-387. doi: 10.4236/ica.2011.24043.