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Model predictive control of air pollution control processes

  • US 7,536,232 B2
  • Filed: 08/27/2004
  • Issued: 05/19/2009
  • Est. Priority Date: 08/27/2004
  • Status: Active Grant
First Claim
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1. A controller for directing operation of an air pollution control system performing a process to control emissions of a pollutant, having multiple process parameters (MPPs), one or more of the MPPs being a controllable process parameters (CTPPs) and one of the MPPs being an amount of the pollutant (AOP) emitted by the system, and having a defined AOP value (AOPV) representing an objective or limit on an actual value (AV) of the emitted AOP, comprising:

  • one of a neural network process model and a non-neural network process model representing a relationship between each of the at least one CTPP and the emitted AOP; and

    a control processor configured with the logic to predict, based on the one model, how changes to a current value of each of at least one of the one or more CTPPs will affect a future AV of emitted AOP, to select one of the changes in one of the at least one CTPP based on the predicted affect of that change and on the AOPV, and to direct control of the one CTPP in accordance with the selected change for that CTPP.

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