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Model Predictive Control for a Distillation Column Model

Satheesh Babu R


Model Predictive Control (MPC) is a multivariable control (requires specific handling of each input as coupling and interaction is of a far greater effect) and uses the internal dynamic model of the process, past control moves and an optimization cost function over the receding prediction horizon, to calculate the optimum control moves. In this paper, the relation between MPC parameters was studied on process constraints. Conical tank level single-input-single-output (SISO) system was taken for real system implementation. For multi-input-multi-output (MIMO) case, distillation column model was taken. It is shown that MPC has constraint handling capabilities, but the choice of control horizon and predictive horizon plays crucial rule for real system implementation


Model Predictive Control, distillation column, control move, predictive move.

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