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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...
This paper describes an intelligence based model predictive control scheme in dealing with a complicated system. In the control strategy proposed here, the system has to be first represented through a multi-Takagi-Sugeno-Kang (TSK) fuzzy-based model approach and subsequently a multi-generalized predictive control (GPC) scheme is realized in line with the investigated model outcomes, at a number of...
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...
This work deals with a novel load-frequency control (LFC) using the fuzzy-based predictive scheme in a two-area interconnected power system. At first, the power system needs to be modeled and subsequently the Takagi-Sugeno-Kang (TSK) fuzzy-based approach using the linear generalized predictive control (LGPC) scheme is realized to implement on the system presented. In order to demonstrate the effectiveness...
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