@misc{Tatjewski_Piotr_Soft,
 author={Tatjewski, Piotr and Ławryńczuk, Maciej},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 abstract={The application of fuzzy reasoning techniques and neural network structures to model-based predictive control (MPC) isstudied. First, basic structures of MPC algorithms are reviewed. Then, applications of fuzzy systems of the Takagi-Sugenotype in explicit and numerical nonlinear MPC algorithms are presented. Next, many techniques using neural networkmodeling to improve structural or computational properties of MPC algorithms are presented and discussed, from a neuralnetwork model of a process in standard MPC structures to modeling parts or entire MPC controllers with neural networks.Finally, a simulation example and conclusions are given.},
 type={artykuł},
 title={Soft computing in model - based predictive control},
 keywords={process control, model predictive control, nonlinear systems, fuzzy systems, neural networks},
}