Computer apparatus and method using model structure information of model predictive control
Abstract:
A system and method of model predictive control executes a model predictive control (MPC) controller of a subject dynamic process (e.g., processing plant) in a configuration mode, identification mode and model adaptation mode. Users input and specify model structure information in the configuration mode, including constraints. Using the specified model structure information in the identification mode, the MPC controller generates linear dynamic models of the subject process. The generated linear dynamic models collectively form a working master model. In model adaptation mode, the MPC controller uses the specified model structure information in a manner that forces control actions based on the formed working master model to closely match real-world behavior of the subject dynamic process. The MPC controller coordinates execution in identification mode and in model adaptation mode to provide adaptive modeling and preserve structural information of the model during a model update.
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