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Adaptive control of HVAC processes using predictive neural networks.

Author(s) : CURTISS P. S., KREIDER J. F., BRANDEMUEHL M. J.

Summary

In practically all HVAC systems, the maintenance of process setpoints relies on feedback loop control. Proportional, integral, and derivative (PID) algorithms are often used in these controllers. The optimization of such loops has been the subject of many studies, most of which use techniques to first model the dynamic behaviour of the process and then to use the model to arrive at a series of control constants that would effect a first-order response to changes in setpoint. The paper demonstrates how artificial neural networks (ANNs) can be used for the same purpose and compares the performance of two types of ANN controllers to a conventional PID controller.

Details

  • Original title: Adaptive control of HVAC processes using predictive neural networks.
  • Record ID : 1994-1123
  • Languages: English
  • Source: ASHRAE Transactions 1993.
  • Publication date: 1993
  • Document available for consultation in the library of the IIR headquarters only.

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