Affiliations: [a] Department of Energy Engineering, Hebei University of Architecture, Zhangjiakou, Hebei, China | [b] Hebei Energy Storage and Heating Technology Innovation Center, Hebei, China
Correspondence:
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Corresponding author: Yong Sun, Department of Energy Engineering, Hebei University of Architecture, Zhangjiakou, Hebei 075000, China. E-mail: [email protected].
Abstract: In the direction of better resolution of time lag, nonlinearity and uncertainty in the heating system, a BPNN-PID (BP neural network PID) controller is proposed in this paper. A complete heating auto-control system is designed with the experimental platform of a university heat exchange station in Zhangjiakou as the research background. The auto-control system takes Programmable Logic Controller (PLC) as the control core, uses BPNN algorithm to optimize the PID control parameters, and finally takes outlet temperature of 1# plate exchanger as the main control parameter to conduct experimental research on BPNN-PID control and single-loop feedback control respectively. The results show that compared with the single-loop feedback controller, the PID control based on BPNN algorithm has superior control quality, with shorter adjustment time, smaller overshoot, finer control accuracy and stability.
