{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:49:29Z","timestamp":1776811769610,"version":"3.51.2"},"reference-count":25,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,12,15]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3233\/jcm-226972","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T12:23:22Z","timestamp":1702988602000},"page":"2851-2866","source":"Crossref","is-referenced-by-count":2,"title":["Application research of BP neural network PID in control system of heat exchange station"],"prefix":"10.66113","volume":"23","author":[{"given":"Chunlei","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Energy Engineering, Hebei University of Architecture, Zhangjiakou, Hebei, China"},{"name":"Hebei Energy Storage and Heating Technology Innovation Center, Hebei, 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