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Development of an on-line adaptive ANN-based controller for a direct expansion air-conditioning system.

Number: pap. 2132

Author(s) : LI N., XIA L., DENG S., et al.

Summary

An on-line adaptive artificial neural network (ANN)-based controller has been developed for an experimental DX A/C system. It controls the indoor air temperature and humidity simultaneously by varying the compressor speed and supply fan speed in a space served by the experimental DX A/C system. The ANN-based direct inverse control strategy was adopted in the development of the controller and the specialized training method was used to on-line update an ANN-based model and an inverse model used in the controller. The controllability tests including the command following test and the disturbance rejection test were carried out using the experimental DX A/C system, and the test results showed that the on-line adaptive ANN-based controller developed was able to control indoor air dry-bulb temperature and wet-bulb temperature outside the operating conditions within which the models were trained, with a high control accuracy.

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Pages: 8 p.

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Details

  • Original title: Development of an on-line adaptive ANN-based controller for a direct expansion air-conditioning system.
  • Record ID : 30006315
  • Languages: English
  • Source: 2012 Purdue Conferences. 14th International Refrigeration and Air-Conditioning Conference at Purdue.
  • Publication date: 2012/07/16

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