Abstract
Numerically efficient analytical MPC (Model Predictive Control) algorithm based on fuzzy Hammerstein models is proposed in the paper. Thanks to the form of the model the prediction can be described by analytical formulas and the proposed algorithm is numerically efficient. It is shown that thanks to a clever tuning of the controller most of calculations needed to derive the control value can be performed off–line. Thus, the proposed algorithm has the advantage reserved so far for analytical MPC algorithms based on linear models. At the same time, the algorithm offers practically the same performance as the MPC algorithm in which a nonlinear optimization problem must be solved at each iteration. The efficiency of the algorithm is demonstrated in the control system of a nonlinear control plant with delay.
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Marusak, P.M. (2011). Numerically Efficient Analytical MPC Algorithm Based on Fuzzy Hammerstein Models. In: Dobnikar, A., Lotrič, U., Šter, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2011. Lecture Notes in Computer Science, vol 6594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20267-4_19
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DOI: https://doi.org/10.1007/978-3-642-20267-4_19
Publisher Name: Springer, Berlin, Heidelberg
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