Neural Networks for Synthesis and Optimization of Antenna Arrays

This paper describes a usual application of back-propagation neural networks for synthesis and optimization of antenna array. The neural network is able to model and to optimize the antennas arrays, by acting on radioelectric or geometric parameters and by taking into account predetermined general criteria. The neural network allows not only establishing important analytical equations for the optimization step, but also a great flexibility between the system parameters in input and output. This step of optimization becomes then possible due to the explicit relation given by the neural network. According to different formulations of the synthesis problem such as acting on the feed law (amplitude and/or phase) and/or space position of the radiating sources, results on antennas arrays synthesis and optimization by neural networks are presented and discussed. However ANN is able to generate very fast the results of synthesis comparing to other approaches

Microstrip antennas array Design Using Genetic algorithms and Simulated Annealing

This publication presents two new approaches of design microstrip antennas array. First is based on the technique of the genetic algorithms inspired from the processes of the evolution of the species and the natural genetics and the second based on the analogy between the resolution of the combinative problems of optimization and the annealing of the solids. These two approaches permits to seek simultaneous the law of optimal feed and the space distribution of the radiant elements so that the radiation pattern is as close as possible to an optimal desired diagram specified from a function or a pattern shape.Cette publication présente deux nouvelles approches de conception de réseaux d'antennes imprimées. La première est basée sur la technique des algorithmes génétiques inspirée des processus de l'évolution des espèces et de la génétique naturelle et la deuxième sur l'analogie entre la résolution des problèmes d'optimisation combinatoire et le recuit des solides. Ces deux approches permettent de rechercher simultanément la loi d'alimentation optimale et la répartition spatiale des éléments rayonnants pour que le diagramme de directivité du réseau soit aussi proche que possible d'un diagramme désiré optimal spécifié à partir d'une fonction ou d'un gabarit

Ceramic Microbial Fuel Cells Stack: Power generation in standard and supercapacitive mode

© 2018 The Author(s). In this work, a microbial fuel cell (MFC) stack containing 28 ceramic MFCs was tested in both standard and supercapacitive modes. The MFCs consisted of carbon veil anodes wrapped around the ceramic separator and air-breathing cathodes based on activated carbon catalyst pressed on a stainless steel mesh. The anodes and cathodes were connected in parallel. The electrolytes utilized had different solution conductivities ranging from 2.0 mScm-1 to 40.1 mScm-1, simulating diverse wastewaters. Polarization curves of MFCs showed a general enhancement in performance with the increase of the electrolyte solution conductivity. The maximum stationary power density was 3.2 mW (3.2 Wm-3) at 2.0 mScm-1 that increased to 10.6 mW (10.6 Wm-3) at the highest solution conductivity (40.1 mScm-1). For the first time, MFCs stack with 1 L operating volume was also tested in supercapacitive mode, where full galvanostatic discharges are presented. Also in the latter case, performance once again improved with the increase in solution conductivity. Particularly, the increase in solution conductivity decreased dramatically the ohmic resistance and therefore the time for complete discharge was elongated, with a resultant increase in power. Maximum power achieved varied between 7.6 mW (7.6 Wm-3) at 2.0 mScm-1 and 27.4 mW (27.4 Wm-3) at 40.1 mScm-1

Controlled Random Search Optimization for Linear Antenna Arrays

An optimization problem for designing nonuniformly spaced, linear antenna's arrays is formulated and solved by means of a controlled random search algorithm. The proposed iterative method aims at a linear array and the optimization of element positions and excitations coefficients by minimizing the side-lobes level and respecting a beam pattern shape. Selected examples are included, which demonstrate the effectiveness and the design flexibility of the proposed method in the framework of the electromagnetic synthesis of linear antenna arrays

Optimization of Micro Strip Array Antennas Using Hybrid Particle Swarm Optimizer with Breeding and Subpopulation for Maximum Side-Lobe Reduction

In this paper, a technique based on hybrid particle swarm optimiser with breeding and subpopulation is presented for optimal design of reconfigurable dual-beam linear array antennas and planar arrays. In the amplitudephase synthesis, the design of a reconfigurable dual-pattern antenna array is based on finding a common amplitude distribution that can generate either a pencil or sector beam power pattern, when the phase distribution of the array is modified appropriately. The goal of this study is to introduce the hybrid model to the electromagnetic community and demonstrate its great potential in electromagnetic optimizations