Abstract
In this paper, the overall framework for chilled water system in heating, ventilation, and air-conditioning (HVAC) system was analyzed, then aiming at the chilled water system, the control loop in secondary pump frequency - pressure difference was identified and the Generalized Prediction Control (GPC) algorithm was designed and deployed for the strategy of fixed pressure difference control. The GPC algorithm adopts multi-step prediction, rolling optimization and feedback correction method to suit a wide range of process. Simulation and experimental results demonstrate that the designed GPC algorithm has obvious advantages in effectiveness and superior performance with strong tracking and anti-jamming capability, compared with conventional manually tuned PID control algorithm.
Highlights
HVAC systems require control of environmental variables such as pressure, temperature, humidity, etc
Step 2: According to the step response of secondary pump frequency – pressure shown in Figure 4, the collected data show that the average delay time is 2.6 seconds and the average transient process time is 2 seconds
The above experimental results show that PID and Generalized Prediction Control (GPC) algorithm has good following performance to step control
Summary
HVAC systems require control of environmental variables such as pressure, temperature, humidity, etc. Tuning a PID controller requires an accurate model of a process and an effective controller design rule. The GPC self-tuning controllers was designed and deployed on the VAV central air conditioning system experimental platform in Intelligent Building Institute in Xi'an University of Architecture and Technology. The Overall Architecture of Chilled Water System in Central Air-Conditioning System The prediction error z (k) is put into identification algorithm and the estimated parameter value ˆ(k) in time k can be calculated under certain rule and the model parameter can be updated. The model output z(k) is the best approximation to system output value z(k) under such criterion to obtain the desired model (Bai & Zhang, 2007; Kusiak & Xu, 2012)
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