Abstract
A long-range model-based predictive control algorithm which is based on the Takagi–Sugeno–Kang piece-wise linear fuzzy modelling approach is proposed. A non-linear multivariable chemical processes represented by a binary distillation column is used as a test-bed for a series of experiments, results of which suggest that the controller performs better than the long-range predictive control algorithm which is based on a linear modelling approach, in terms of effective set-point tracking and interactions handling.
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