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A parametric dynamic matrix controller approach for nonlinear chemical processes

Abstract:

This study presents a Parametric Dynamic Matrix Controller (PDMCr) to handle independently the process gain, time constant and dead time effects over the DMC performance. The controller is complemented with a fuzzy supervisory module that monitors changes on the process nonlinear behavior and keeps updated the embedded process model, saving time by avoiding repeating the open-loop step response identification. The new PDMCr is able to improve regulation and control tasks, even in those cases when the operation point is far from the initial identification point. Three examples are used to assess the PDMCr performance, a linear FOPDT and two nonlinear chemical processes: a mixing tank, and a neutralization reactor. The PDMCr improves the DMC performance, tracking set point and rejecting disturbances with shorter settling times and less overshoot, it remains stable when DMCr oscillates; and show more tolerance to noise than the DMCr, keeping a stable behavior for longer times under noisy input signals. When both performances are comparable, the IAE values for the PDMCr are until 23% lower compared to the DMCr.