Title :
Dynamic neural network based nonlinear adaptive control for a distillation column
Author :
Shurong, LI ; Feng, LI
Author_Institution :
Univ. of Pet., Dongying, China
Abstract :
In this paper, a dynamic neural network is used to learn the input-output behaviors of a binary distillation column by combining the mechanistic property. The model can be online identified. The weight-training algorithm is proposed. The convergence of the algorithm is discussed by using the Lyapunov method. Based on the identified model, a nonlinear adaptive controller is designed, which can preserve the stability and robustness of the closed loop system. Some simulation results are illustrated to show the effectiveness of the controller
Keywords :
Lyapunov methods; adaptive control; closed loop systems; convergence; distillation; neurocontrollers; nonlinear control systems; process control; stability; Lyapunov method; adaptive control; closed loop system; convergence; distillation column; dynamic neural network; nonlinear control systems; robustness; stability; weight-learning algorithm; Adaptive control; Convergence; Distillation equipment; Lyapunov method; Mechanical factors; Neural networks; Nonlinear control systems; Programmable control; Robust control; Robust stability;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863026
