Innovations in generalized predictive control using TSK fuzzy-based approach

The main idea of the paper presented here is to reorganize the linear model based generalized predictive control (LGPC) approach in dealing with a severe nonlinear system. The proposed control strategy is investigated using a TSK fuzzy-based LGPC approach as well as a TSK fuzzy-based model approach. The TSK fuzzy-based model approach is accurately identified as the best representation of the nonlinear system, at each instant of time. And subsequently the TSK fuzzy-based LGPC approach is realized in line with the system modeling outcomes. In order to present the validity of the proposed control strategy, the simulations are carried out in deriving an industrial tubular heat exchanger system as a highly nonlinear system. As is obvious from its acquired results, the proposed control strategy is appropriate in comparison with the traditional LGPC approach.