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Predictive Control Of Nonlinear Processes Using Fuzzy Hammerstein Model

Zuzana Didekova, Slavomir Kajan, Štefan Kozák
In this paper a novel methodology for modeling and control of a class of nonlinear systems is proposed. The non-linear system is modeled by the so-called fuzzy Hammerstein model, and the control strategy based on generalized predictive control (GPC) algorithm is applied. Simulation of a modified DC motor with a nonlinear block demonstrates effectiveness of the proposed approach. The proposed control is compared with other predictive control approaches based on artificial neural network models. Obtained results confirm that the proposed methodology can be used for modeling and control of different types of nonlinear processes in industry applications.
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