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IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Abushawish, Abdallah Jarndal, Anwar Univ Sharjah Elect Engn Dept Sharjah U Arab Emirates

ISBN: (纸本)9781665424615

In this research, four topologies have been investigated to characterize substrate/buffer loading effect on GaN HEMT on Si. This effect has been simulated using open deembedded structure's Z-parameter measurements for GaN HEMT on Si. An optimization technique based on Grey Wolf Optimization (GWO) with Cuckoo Search (CS) has been developed to extract four models' elements. The simulated data fitting compared with the measured one has been considered the validation of the process. The models are evaluated in terms of rate of convergence to minimum error and accuracy of the results. The results showed good agreement with previous literature.

关键词： GaN HEMT substrate/buffer loading effect Grey Wolf Optimization (GWO) Cuckoo Search (CS) open de-embedding structure small-signal model

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Comparison of GA, GWO, and HHO Optimization Techniques for Modeling Substrate/Buffer Loading Effect on GaN HEMTs 14

Comparison of GA, GWO, and HHO Optimization Techniques for M...

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14th International Conference on developments in eSystems Engineering (deSE)

作者： Abushawish, Abdallah Jarndal, Anwar Univ Sharjah Elect Engn Dept Sharjah U Arab Emirates

ISBN: (纸本)9781665408882

In this research, a comparison between three optimization techniques in the context of hybrid-direct extraction of GaN on Si HEMTs elements that characterize the substrate/buffer loading effect has been developed. The optimization techniques used are Genetic Algorithm (GA), Grey Wolf Optimization (GWO), and Harris-Hawks Optimization (HHO). The open de-embedded structure's Z-parameter have been used to simulate this effect on GaN on Si HEMTs devices. Comparing the measured Z-parameters with the simulated ones has been considered the validation of the techniques. The convergence speed and extraction time have been utilized for the evaluation of the techniques' efficiencies. The results showed the advantage of GWO in terms of fitting error and convergence speed.

关键词： component GaN HEMT Grey Wolf Optimization (GWO) Genetic Algorithm (GA) Harris-Hawks Optimization open de-embedding structure small-signal model substrate/buffer loading effect

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On modeling of substrate loading in GaN HEMT using grey wolf algorithm

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JOURNAL OF COMPUTATIONAL ELECTRONICS 2020年第2期19卷 576-590页

作者： Jarndal, Anwar Univ Sharjah Elect Engn Dept Sharjah 27272 U Arab Emirates

In this paper, four different equivalent circuit models to describe substrate loading effect in GaN HEMT on Si substrate are investigated. The effect is characterized by Z-parameter measurements of open de-embedding structure for 16 x 200-mu m GaN HEMT on Si substrate. The grey wolf optimization (GWO)-based procedure is developed to extract optimal values for the model elements. The performance of the proposed technique is evaluated by using two other meta-heuristic optimizations, the well-known particle swarm and the recently developed whale algorithm. The three extraction procedures are evaluated in terms of their effectiveness and rate of convergences. The models are validated by means of S-parameters simulation for the considered device at different passive and active bias conditions. A very good agreement with measurements is achieved when using the GWO, validating its applicability for small- and large-signal modeling applications.

关键词： Grey wolf optimizer Whale optimization algorithm Particle swarm optimization GaN HEMT open de-embedding structure Substrate loading

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