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://www.zbc.uz.zgora.pl/Content/46818/1tatj.pdf
L2 - http://www.zbc.uz.zgora.pl/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://www.zbc.uz.zgora.pl/dlibra/docmetadata?id=46818
ER -