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
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