Nonlinear Model-Based Predictive Control Using a Generalised Hammerstein Model and its Application to a Semi-Batch Reactor |
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Authors: | RB Abdennour M Ksouri F M'Sahli |
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Affiliation: | (1) Institut Supèrieur des Etudes Technologiques de Ksar-Hellal, Ksar Hellal, Tunisia, TN;(2) Ecole Nationale d’Ingènieurs de Gabes, Universitè de Sfax, Gabes, Tunisia;, TN;(3) Institut National des Sciences Appliquèes et de Technologie, Tunis, Tunisia, TN |
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Abstract: | In recent years, much attention has been focused upon predictive control of nonlinear systems. The implementation of such
a control strategy for real processes has greatly improved their performance. This paper deals with a model-based predictivecontrol
(MBPC) strategy using a generalised Hammerstein model and its application to the temperature control of a semibatch reactor.
Both unconstrained and constrained adaptive control problems are considered. A simple identification method based on the weighted
recursive least squares method (WRLS) is used to estimate the model parameters on-line. An indirect adaptive nonlinear controller
is designed by combining the predictive controller with an indirect parameter estimation algorithm. This adaptive scheme
has been applied for the control of a semi-batch chemical reactor. Experimental results show that the performance of the generalised
Hammerstein MBPC (NLMBPC) was significantly better than that of a linear model predictive controller (LMBPC).
ID="A1"Correspondance and offprint requests to: Dr F. M'sahli, Department of Electrical Engineering, ISETKH, Avenue Hadj Ali Soua, 5070, Ksar Hellal, Monastir, Tunisia.
E-mail: msahli-fn@iyahoo.fr |
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Keywords: | : Adaptive predictive control Generalised Ham-merstein model Nonlinear control Reactor |
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