Soft computing in model - based predictive control - Tatjewski, Piotr; Ławryńczuk, Maciej (Zielona Góra: Uniwersytet Zielonogórski)
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.
Keywords: process control; model predictive control; nonlinear systems; fuzzy systems; neural networks