Experimental study of suppression and blocking in internal model control
Abstract
One of most popular tuning methods currently used for tuning controllers based on convolution models is the suppression of the variation of the control action after a certain sampling time in the predictive horizon. In this paper an alternative tuning method is studied. This method is based on keeping the control action constant over blocks of sampling times in the predictive horizon. Experimental results are presented on the performance of both tuning methods. These results show that the IMC controller with blocking action compares favorably with the suppression method, and that the combination of penalizing variations of the control action and blocking is the most convenient tuning alternative.
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