Ekrem ÇALIŞKAN, Fevzullah TEMURTAŞ, Nejat YUMUŞAK

Fuzzy inference systems for gas concentration estimation

Bu çalışmada, Mamdani ve Sugeno bulanık sonuç çıkarım sistemleri (BSÇS) kararlı hal sensor cevapları kullanılarak Totuen gazının konsantrasyon tahmini için kullanılmış ve sunulmuştur. Bir yapay sinir ağı (YSA) yapısıda ayrıca mukayese için kullanılmıştır.Gaz sensörü olarak Kuartz Kristal Mikrobalans tip sensor kullanılmıştır. BSÇS ve YSA ile yapılan konsantrasyon tahminlerinde kabul edilebilir performanslar elde edilmiştir. Sonuçlar gaz konsantrasyon tahmini için Sugeno BSÇS'nin Mamdani BSÇS'den daha iyi performans sağladığını göstermektedir. Sugeno BSÇS'nin tahmin sonuçlan YSA'nm tahmin sonuçlarına oldukça yakındır.

In this study, Mamdani's and Sugeno's fuzzy inference systems (FIS) is presented for the concentration estimation of the Toluene gas by using the steady state sensor response. An artificial Neural Network (ANN) structure is also used for comparison. The Quartz Crystal Microbalance (QCM) type sensors were used as gas sensors. Acceptable performances were obtained for the concentration estimation with FISs and ANN. The results show that Sugeno's FIS performs better than Mamdani's FIS for gas concentration estimation. The estimation results of Sugeno's FIS are very closer to estimation results of ANN.

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