An Evolutionary Method for Synthesizing Low-Sensitivity Lossless Matching Networks

Whereas the present practice of designing matching networks for antennas is limited to conventional topologies, requiring a significant amount of domain knowledge, evolutionary algorithms can be used for automatically identifying unconventional designs that are more effective than would otherwise be developed. In this work, an automatic method to design lossless matching networks driven by an evolutionary algorithm (EA) that considers the sensitivities of the network parameters during the synthesis process is presented. To this end, a closed-form expression for the transducer power gain (TPG) sensitivity with respect to the component values is employed in such a way that the effects of the components tolerance on the matching network performance can easily be quantified. A 3D data structure based on the adjacency matrix is conveniently used to represent any type of network topologies. The proposed EA employs a novel set of topology variation operators, tailored for changing the circuit topology, and an association step, with the aim of reducing the number of nodes of the matching circuit. The efficiency of the proposed EA is tested in the synthesis of an impedance matching network for a VHF monopole whip antenna. This study's results indicate a matching bandwidth improvement, a more uniformly distributed TPG along the operation frequency band and a more stable TPG regarding the components tolerance compared to the results obtained by previous approaches.