Genetic Particle Swarm Optimization-based Impedance Matching Method for RF Power Amplifiers
In practical work,the load characteristics of RF power sources change rapidly,which leads to impedance mismatch and the output power of the power source cannot always be at the rated value.To overcome this phenomenon,real-time impedance matching of time-varying loads is necessary.This paper proposes a genetic particle swarm optimization-based impedance matching method for RF power sources.Firstly,particles representing the variable component parameters in the impedance matching network are subjected to cross-over and mutation operations to increase particle diversity.At the same time,nonlinearly decreasing inertia weight and dynamic learning factors are introduced to adjust the search range according to the particle optimization situation,and the optimal solution of the impedance matching network parameters can be obtained with only a small number of iterations,improving the optimization speed.The simulation results show that the fusion algorithm is superior to traditional particle swarm algorithms and genetic algorithms in terms of impedance matching real-time performance and accuracy.
radio frequency power supplyimpedance matchinggenetic particle swarm fusiondynamic learning factornonlinear decreasing inertia weight
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