DocumentCode
382394
Title
Neurofuzzy model based l∞ predictive control of nonlinear CSTR system
Author
Wu, Q. ; Wang, Y.J. ; Zhu, Q.M. ; Warwick, K.
Author_Institution
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume
1
fYear
2002
fDate
2002
Firstpage
59
Abstract
In this paper the nonlinear dynamics of a continuously stirred tank reactor (CSTR) are modelled with a neuro-fuzzy network, so that a predictive control strategy is developed based on the l∞ norm performance. Stability of the closed loop system is proved that the system is stable if each local linear control system is closed loop stable. The pH control in neutralisation process within the CSTR was simulated to indicate that the control performance is superior to that from quadratic predictive control.
Keywords
chemical industry; closed loop systems; fuzzy neural nets; nonlinear control systems; optimal control; pH control; predictive control; process control; stability; CSTR system; closed loop system; continuously stirred tank reactor; fuzzy neural network; neutralisation; nonlinear system; pH control; predictive control; stability; Closed loop systems; Continuous-stirred tank reactor; Control systems; Fuzzy neural networks; Inductors; Nonlinear dynamical systems; Predictive control; Predictive models; Process control; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Applications, 2002. Proceedings of the 2002 International Conference on
Print_ISBN
0-7803-7386-3
Type
conf
DOI
10.1109/CCA.2002.1040160
Filename
1040160
Link To Document