EFFICIENT FUZZY PREDICTIVE ALGORITHMS WITH INTEGRATED ECONOMIC OPTIMIZATION: A CASE STUDY

In the paper model predictive control algorithms with integrated economic optimization based on a nonlinear, fuzzy dynamic control plant models instead of a linear ones are proposed. Such an approach leads to achievement of better control performance. In the proposed algorithms Takagi–Sugeno fuzzy models with step response local models are used. Thanks to such an approach the process model can be obtained in an easy way, as it was demonstrated during the design of the control algorithm for an example MIMO control plant. The results obtained in the example control system clearly illustrate advantages of the proposed fuzzy algorithms.