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Non-linear predictive control

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2 Author(s)
E. Katende ; Dept. of Chem. & Biochem. Eng., Univ. of Western Ontario, London, Ont., Canada ; A. Jutan

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

Published in:

American Control Conference, Proceedings of the 1995  (Volume:6 )

Date of Conference:

21-23 Jun 1995