通過(guò)對(duì)國(guó)內(nèi)加熱爐控制現(xiàn)狀及技術(shù)難點(diǎn)的分析，提出采用非線性的模糊控制與線性的PI控制相結(jié)合的雙模態(tài)爐溫控制方案，運(yùn)用神經(jīng)網(wǎng)絡(luò)空燃配比尋優(yōu)技術(shù)實(shí)現(xiàn)燃燒的最佳化，設(shè)計(jì)基于數(shù)學(xué)模型與操作經(jīng)驗(yàn)的專家系統(tǒng)解決各段爐溫的自動(dòng)設(shè)定問(wèn)題，從而實(shí)現(xiàn)了對(duì)整個(gè)加熱過(guò)程的全自動(dòng)智能控制。實(shí)際運(yùn)行結(jié)果表明，該系統(tǒng)可靠性強(qiáng)，控制精度高，節(jié)能效果明顯，對(duì)工業(yè)爐窯的控制具有一定的推廣價(jià)值。
關(guān)鍵詞：加熱爐模糊控制神經(jīng)網(wǎng)絡(luò) 智能控制
The Heat Treatment Furnace Automation System Based On Intelligent Control
Pan Haipeng (Department of Automation, Zhejiang Institute of Science and Technology, Hangzhou 310033) Abstract: Through the analysis of current status and technique difficulties for Heat Treatment Furnace control, this paper puts forward a new plan that combines nonlinear fuzzy controllers with linear PI controlers to control furnace temperature. By NN empty combustion dosing ratio optimization technique to realize combustion optimization. This paper resolves automatic temperature setting of furnace for every segment based on mathematics model and expert system. Then the automatic intelligent control of the whole heating process is realized. Application shows that the system has good reliability, high control precision and obvious energy conservation effect. The results can be extended in industry heating furnace control.
Keywords: Heat Treatment Furnace, fuzzy control, NN( neural network), intelligent control