Title :
Adaptive Feedback-Feedforward Control for a Class of Nonlinear Chemical Processes
Author :
Li Jia ; Chiu, Min-Sen
Author_Institution :
Shanghai Key Lab. of Power Station Autom. Technol., Shanghai Univ.
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
To circumvent the drawbacks in nonlinear controller designing of chemical processes, an adaptive feedback-feedforward control scheme is proposed in this paper. A class of nonlinear processes with modest nonlinearities is approximated by a composite model consisting a linear ARX model and a fuzzy neural network-based linearization error model. In addition, the stable analysis is also discussed. Simulation results show that the feedforward control plays a major role in improving the control performance, and the proposed feedback-feedforward control possesses better performance
Keywords :
adaptive control; chemical engineering; control system synthesis; feedback; feedforward; fuzzy control; fuzzy neural nets; linearisation techniques; neurocontrollers; nonlinear control systems; process control; adaptive feedback-feedforward control; fuzzy neural network-based linearization error model; linear ARX model; nonlinear chemical process; nonlinear controller design; Adaptive control; Automatic control; Chemical processes; Chemical technology; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Linear feedback control systems; Neural networks; Programmable control;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.36