Vasylenko D. Structural synthesis of planar antennas by nature inspired optimization algorithms

An efficiency of the constructive synthesis is numerically investigated for the ultrawideband dipole antenna and tapered slot antenna for the frequency range 3.1-10.6 GHz and microstrip antenna for receiving GPS signals at frequency 1.575 GHz. The goal of the synthesis is achieved by properly modifying the radiating contour profile of the mentioned antennas. In this investigation the maximum number of points along the contour is 10. It is established that particle swarm optimization needs to analyze in the method of moments based full-wave simulation program FEKO 3-4 times less number of antenna variants than genetic algorithm and it is found an optimum set of parameters for the investigated global optimization algorithms. In order to reduce synthesis time a novel concept of neural-genetic optimization is presented. The key feature of this algorithm is modeling of the antenna by using artificial neural networks (ANN) with a modular architecture and synthesis by inversion of the created ANN by using genetic algorithm. It is found that model of the antenna with the error on the level of "engineering precision" 10% for both gain and return loss can be created by using a multi-layer perceptron with three hidden layers with 10 to 20 neurons in each and sigmoid activation function in the form of hyperbolic tangent. A combination of Levenberg-Marquardt backpropagation algorithm with Bayesian regularization is found to have the best performance on training of the neural networks. In order to illustrate a neural-genetic algorithm an UWB planar dipole and an UWB planar tapered slot antenna are optimized with respect to return loss and gain. The optimized antennas shows a good impedance matching (return loss < -10 dB) and gain 2 to 5 dB for the dipole antenna and 5 to 10 dB for the tapered slot antenna over the whole frequency range. Through the synthesis of the orthomode transducer for the frequency range 3.4 - 4.2 GHz, return loss less than 0.1 and channel isolation more than 40 dB it is shown that neural-genetic algorithm can be applied for synthesis of microwave devices as well.