Abstract
Efficient Model Predictive Control (MPC) algorithms based on fuzzy Wiener models are proposed in the paper. Thanks to the form of the model the prediction of the control plant output can be easily obtained. It is done in such a way that the MPC algorithm is formulated as a numerically efficient quadratic optimization problem. Moreover, inversion of the static process model, used in other approaches, is avoided. Despite its relative simplicity the algorithm offers practically the same performance as the MPC algorithm in which control signals are generated after solving a nonlinear optimization problem and outperforms the MPC algorithm based on a linear model. The efficacy of the proposed approach is demonstrated in the control system of a nonlinear control plant.
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Marusak, P.M. (2010). Application of Fuzzy Wiener Models in Efficient MPC Algorithms. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds) Rough Sets and Current Trends in Computing. RSCTC 2010. Lecture Notes in Computer Science(), vol 6086. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13529-3_71
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DOI: https://doi.org/10.1007/978-3-642-13529-3_71
Publisher Name: Springer, Berlin, Heidelberg
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