Design of an intelligent control scheme based on predictive theory

This research work describes an intelligent control scheme for deriving a severe nonlinear system via the predictive control theory. In line with the control scheme proposed, the system behavior is first represented by a multilinear model approach (MLA), while a multi-GPC approach (MGA) is realized based on acquired outcomes. Subsequently, an intelligent decision maker system (IDMS) is realized to derive both the MGA and the MLA, at each instant of time. In this control scheme, the desirable control action in correspondence with the system behavior is instantly updated to apply to the system. In order to display the effectiveness of the proposed control scheme, simulations are carried out and its results are compared with those obtained using the traditional predictive control scheme, as a benchmark approach. The results verify the validity of the control scheme proposed in comparison with the previous one.