A neural control method for impedance matching of antenna systems

The primary intent of this paper is real-time compensation for changes in the driving point impedance of an antenna due to frequency deviations. In general, the driving point impedance of an antenna or antenna array is computed by numerical methods such as the method of moments or similar techniques. Some configurations do lend themselves to analytical solutions, which will be the primary focus of this work. This paper employs a neural control system to match antenna feed lines to two common antennas during frequency sweeps. In practice, impedance matching is performed off-line with Smith charts or relatively complex formulas but they rarely perform optimally over a large bandwidth. The approach proposed here employs three small neural networks to perform real-time impedance matching over a broad range of frequencies during transmitter operation. Double stub tuners are being explored in this paper but the approach can certainly be applied to other methodologies.