TY - GEN A1 - Tatjewski, Piotr A1 - Ławryńczuk, Maciej A2 - Korbicz, Józef - red. PB - Zielona Góra: Uniwersytet Zielonogórski N2 - 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. L1 - http://zbc.uz.zgora.pl/repozytorium/Content/46818/1tatj.pdf L2 - http://zbc.uz.zgora.pl/repozytorium/Content/46818 KW - process control KW - model predictive control KW - nonlinear systems KW - fuzzy systems KW - neural networks T1 - Soft computing in model - based predictive control UR - http://zbc.uz.zgora.pl/repozytorium/dlibra/docmetadata?id=46818 ER -