A case study for fuzzy adaptive multiple models predictive control strategy

The purpose of the paper presented here is to deal with the well-known linear generalized predictive control (LGPC) scheme based on multiple models strategy for a tubular heat exchanger system. In this control strategy, the operating environments of the system are first represented by multiple explicit linear models. Then the best model of the system is precisely identified by a novel intelligent decision mechanism (IDM), where is organized in association with the fuzzy adaptive Kalman filter and recursive weight generator approaches. As soon as the best model of the system is identified, the corresponding predictive control action is instantly implemented on the system. In order to demonstrate the effectiveness of the proposed strategy, simulations are carried out and the outcomes are compared with those obtained using the nonlinear GPC (NLGPC) approach. The results can verify the validity of the proposed control scheme.