In this letter, the particle swarm optimization (PSO) is employed to optimize the threshold values of the canonical section-wise piecewise linear (CSWPL) function-based behavioral model of power transistors. The effectiveness of the proposed method is validated through measurements carried out on a 10-W GaN power transistor produced by Wolfspeed. Compared with the existing simultaneous perturbation stochastic approximation (SPSA) method, the developed modeling technique not only provides superior prediction performance across different input power levels but also finds the optimal thresholds much more efficiently.

Threshold Optimized CSWPL Behavioral Model for RF Power Transistors Based on Particle Swarm Algorithm

Crupi G.
Penultimo
;
2023-01-01

Abstract

In this letter, the particle swarm optimization (PSO) is employed to optimize the threshold values of the canonical section-wise piecewise linear (CSWPL) function-based behavioral model of power transistors. The effectiveness of the proposed method is validated through measurements carried out on a 10-W GaN power transistor produced by Wolfspeed. Compared with the existing simultaneous perturbation stochastic approximation (SPSA) method, the developed modeling technique not only provides superior prediction performance across different input power levels but also finds the optimal thresholds much more efficiently.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3252557
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