Superfluous model parameters of dynamicmatrix control(DMC) lead to a heavy computationalburden in the computation of process predictive output andonline receding horizon optimization. To overcome theabove demerits of ...
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Superfluous model parameters of dynamicmatrix control(DMC) lead to a heavy computationalburden in the computation of process predictive output andonline receding horizon optimization. To overcome theabove demerits of DMC, a fast algorithm of constrainedDMC is presented in this paper on the basis of stepresponse, by employing a model with fewer redundantparameters to approach step response of a plant. Becauseof far fewer parameters of the redundant-parameter modelthan non-parameterized models, the computational burdenof multi-step prediction and online receding horizonoptimization is greatly lightened. The effectiveness of thepresented algorithm is demonstrated by computersimulations by employing step response data collectingfrom a heat exchanger of a hot-water network.
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