Abstract
This research work looks at methods for controlling a two-phase distillation column system. The present system consists of a vertical column with a number of trays used for component separation. It also has a reboiler and a condenser; these are used to provide heating and cooling for vaporization and condensation, respectively. The proposed control scheme uses the model-based predictive control (MBPC) scheme with the internal model being produced by a set of Takagi Sugeno Kang (TSK) fuzzy-based models. The internal set of TSK fuzzy-based models are developed from a linear models predictive approach. That is, it makes a prediction of the present system using a set of TSK fuzzy-based models identified, at each instant of time. The control scheme is then evaluated using simulation and compared with a benchmark fuzzy-based PI control scheme. The novelty of the present research is to propose a new organization in system modeling and its control scheme by combining the MBPC scheme and artificial intelligence (AI)-based techniques for the purpose of improving the system performance results.
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