Multi-Model Decoupled Generic Model Control

Authors

James B. Riggs
Peter L. Lee

ABSTRACT

The control performance of GMC (Generic Model Control) using steady-state models parameter systems can be significantly undermined by the lack of appropriate dynamic information. A decoupling strategy has been integrated into the GMC framework in order to compensate for dynamic mismatch. The approach (Multi-Model Decoupler, MMD) is based upon using a separate model inverse for the calculation of each manipulated variable. The additional model inputs provide the extra degrees of freedom that allow for dynamic compensation. Because the same model inverse is used for the calculation of each manipulated variable, the model inverse must be evaluated more often than conventional GMC would require. MMD-GMC has the advantage over conventional decouplers since the MMD decoupling elements have unity gain and thus take full advantage of the nonlinear prediction capability of the model controller model. An alternative approach using more traditional External Decouplers (ED-GMC) is developed and compared to MMD-GMC.

Both approaches are demonstrated on a simulation of a high relative volatility binary column. MMD-GMC is shown to offer significant control performance advantages over both ED-GMC and GMC based on steady-state models and no dynamic compensation.

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