Combining Intelligence with Rules for Device Modeling: Approximating the Behavior of AlGaN/GaN HEMTs Using a Hybrid Neural Network and Fuzzy Logic Inference System
Khusro A. Husain S. Hashmi M.S.
2024Institute of Electrical and Electronics Engineers Inc.
IEEE Journal of the Electron Devices Society
2024#12723 - 737 pp.
This paper uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) to investigate and propose a new alternative behavioral modeling technique for microwave power transistors. Utilizing measured I-V characteristics, associated parameters like transconductance (gm) and output conductance (gds), etc., S-parameters characteristics, and RF performance parameters such as unity current gain frequency (fT), maximum unilateral gain frequency (fmax), ANFIS-based behavioral models are developed for Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs) and validated. The models have been developed using two distinct devices with dimensions of 10×200μm and 10×250μm for multi-bias conditions and over a broad frequency range (0.5 to 43.5 GHz). Subsequently, the proposed model performance is validated on devices with geometries of 10×220μm, 4×100μm, and 2×200μm to examine the interpolation accuracy, extrapolation potential, and scalability. Here, ANFIS utilizes the subtractive clustering method to process the measurement characteristics by computing the clusters and opts for the best-performing model using error and number of fuzzy rules as criteria. The parameters involved in the fuzzy representation are trained using neural network algorithms, namely gradient-descent and least squares estimate. The proposed models are subsequently incorporated in a commercial circuit simulator (Keysights ADS) and the class-F power amplifiers gain and stability characteristics are computed and studied.
ANFIS , artificial intelligence , behavioral device modeling , fuzzy logic , GaN HEMTs , neural networks , RF power amplifiers
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Nazarbayev University, School of Engineering and Digital Sciences, Astana, 010000, Kazakhstan
Nazarbayev University
10 лет помогаем публиковать статьи Международный издатель
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