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On-Line Adaptation of Predictive Controllers

Although predictive control techniques such as Dynamic Matrix Control and Model Algorithmic Control have received much attention in recent years, systematic methods for on-line updating of the process models and predictive control laws rarely have been reported. Such adaptation is desirable if the process conditions change significantly over a period of time. The same approach also could be used to generate a discrete convolution model for the initil controller design. In this paper, several alternative strategies for on-line adaptation during closed-loop operation are evaluated and compared via simulations.