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A neural-network-based identifier/controller for modern HVAC control

Conference ·
OSTI ID:211785
;  [1];  [2];
  1. City Univ. of Hong Kong, Kowloon (Hong Kong)
  2. Hong Kong Polytechnic Univ. (Hong Kong)

This paper reports the application of an artificial neural network (ANN) to serve both as a system identifier and as an intelligent controller for an air-handling system. A comprehensive software model has been established based on the specifications of a standard air-handling unit (AHU) on the market. The model is appropriate for testing various control algorithms including the new ANN identifier/controller. The ANN behaves as an identifier by continuously keeping track of all the real-time parameters associated with the whole air-handling system. Five actuating signals are produced based on the nonlinear error optimization of the outputs of the ANN, now served as a controller. The control target involves the minimization of two weighted factors--the errors between setpoints and control variables and the total energy consumption. The excellent performance of the ANN identifier/controller is illustrated by comparing it with that of a conventional proportional-integral-derivative (PID) controller.

OSTI ID:
211785
Report Number(s):
CONF-950624--
Country of Publication:
United States
Language:
English

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