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In this paper an improved Gray-Wolf-Optimization (GWO) based small-signal modeling is developed. The proposed method is demonstrated by modeling GaN High Electron Mobility Transistors (HEMTs) on SiC and Diamond substrates. The technique bases on engineering the optimization objective function to provide reliable values for the model parameters; while keeping a better fitting for the targeted measurements. The reliability of extraction has been further improved by using physical relevant condition to remove any unrealistic values during the optimization process. The modeling procedure was applied on 2x50-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>, 8x150-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>, 8x250-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> and 16x250-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> GaN HEMTs on SiC substrate in addition to 2x125-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> and 4x125-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> GaN HEMTs on Diamond substrate. Very good results were obtained for both technologies with an excellent fitting for the related measurements. The results also show the reliability of the developed technique and validate its applicability for small- and large-signal modeling applications.

Gray Wolf Optimization-Based Modeling Technique Applied to GaN High Mobility Electron Transistors