DocumentCode :
2339269
Title :
Non-linear predictive control
Author :
Katende, Edward ; Jutan, Arthur
Author_Institution :
Dept. of Chem. & Biochem. Eng., Univ. of Western Ontario, London, Ont., Canada
Volume :
6
fYear :
1995
fDate :
21-23 Jun 1995
Firstpage :
4199
Abstract :
Most predictive control algorithms, including the generalized predictive control (GPC),are based on linear dynamics. Many processes are severely nonlinear and would require high order linear approximations. Another approach, which is presented here, is to extend the basic adaptive GPC algorithm to a nonlinear form. This provides a nonlinear predictive controller which is shown to be very effective in the control of processes with nonlinearities that can be suitably modelled using general Volterra and Hammerstein models and bilinear models. Simulations are presented using a number of examples
Keywords :
Volterra equations; nonlinear control systems; predictive control; bilinear models; general Hammerstein models; general Volterra models; nonlinear predictive control; Adaptive control; Control systems; Nonlinear control systems; Polynomials; Prediction algorithms; Predictive control; Predictive models; Programmable control; Temperature control; Thickness control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
Type :
conf
DOI :
10.1109/ACC.1995.532723
Filename :
532723
Link To Document :
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