外文翻譯--蒸汽發(fā)生器水位模糊控制研究-免費閱讀
【正文】 可以看出，與傳統(tǒng) PID 控制相比，模糊控制在超調(diào)量、調(diào)節(jié)時間和穩(wěn)態(tài)特性方面有重要的改善。 中國秦山核電站的一個壓水堆蒸汽發(fā)生器有如下的實驗?zāi)Ｐ停? 其中， Ps 表示額定的負荷。 (2)模糊理論、模糊子集和隸屬函數(shù) e、 ec 和 u 的模糊論域是 [6, 6]，用 NB（負大 ）、 NM（負中）、 NS（負小）、 ZO（零）、 PS（正?。?PM（正中）和 PB（正大） 7個模糊子集描述。 綜上所述，當(dāng)給水流量或者蒸汽負荷變化，水位不會立即跟隨變化，開始會出現(xiàn)一個相反的過程。 壓水堆蒸汽發(fā)生器一般形式的數(shù)學(xué)模型的傳遞函數(shù)如下所示 : y(s)=GW(s)QW(s)+GS(s)QS(s) （ 1） 其中， y 代表蒸汽發(fā)生器的水位； QW 代表給水流量； QS 代表蒸汽流量；GW 代表給水流量對蒸汽發(fā)生器水位的作用； GS 代表蒸汽流量對蒸汽發(fā)生器的水位的作用。正是由于“虛假液位”的存在使得水位控制變得困難。 the bubble volume on the liquid surface increases, causing the water level increased. Comprehensive two factors, after the step increase of the steam flow rate, the water level down has a time delay process, showing a up then down. The impact on the water level of water flow or steam flow stepping decreased has similar principle as above. As analysis can be seen as above, when the water flow or steam load change, the water level did not follow the change immediately, but there is an opposite process at first. This phenomenon is called false water level phenomenon. III. DESIGN OF WATER LEVEL FUZZY CONTROLLER The conventional PID controller has a poor control performance to the steam generator that exist“ false water level” characteristics, showing a greater overshoot in the tracking time. But a welldesigned fuzzy controller is able to overe the false water level phenomenon, and has good control performance. A. Sstructure of Fuzzy Controller The structure showed in Figure 1. Choose the water level error (e) and change rate of error (ec) as input of the fuzzy controller, the output of the fuzzy controller is the added value of the valve opening signal Δu. Meanwhile, use the steam flow feedforward to overe the false water level phenomenon, use water flow feedback to overe fluctuations in water supply side . k1, k2 were water flow and steam flow transmitter conversion factor. To ensure the water flow to match the steam flow, k1 and k2 values should be equal to. B. Fuzzy theory, fuzzy subset and Membership Function The fuzzy Analects of e, ec and u are [6, 6], both with seven fuzzy sets NB (negative big), NM (
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