Multiobjective optimization of electromagnetic structures based on self-organizing migration

Práce se zabývá popisem nového stochastického vícekriteriálního optimalizačního algoritmu MOSOMA (Multiobjective Self-Organizing Migrating Algorithm). Je zde ukázáno, že algoritmus je schopen řešit nejrůznější typy optimalizačních úloh (s jakýmkoli počtem kritérií, s i bez omezujících podmínek, se spojitým i diskrétním stavovým prostorem). Výsledky algoritmu jsou srovnány s dalšími běžně používanými metodami pro vícekriteriální optimalizaci na velké sadě testovacích úloh. Uvedli jsme novou techniku pro výpočet metriky rozprostření (spread) založené na hledání minimální kostry grafu (Minimum Spanning Tree) pro problémy mající více než dvě kritéria. Doporučené hodnoty pro parametry řídící běh algoritmu byly určeny na základě výsledků jejich citlivostní analýzy. Algoritmus MOSOMA je dále úspěšně použit pro řešení různých návrhových úloh z oblasti elektromagnetismu (návrh Yagi-Uda antény a dielektrických filtrů, adaptivní řízení vyzařovaného svazku v časové oblasti…).This thesis describes a novel stochastic multi-objective optimization algorithm called MOSOMA (Multi-Objective Self-Organizing Migrating Algorithm). It is shown that MOSOMA is able to solve various types of multi-objective optimization problems (with any number of objectives, unconstrained or constrained problems, with continuous or discrete decision space). The efficiency of MOSOMA is compared with other commonly used optimization techniques on a large suite of test problems. The new procedure based on finding of minimum spanning tree for computing the spread metric for problems with more than two objectives is proposed. Recommended values of parameters controlling the run of MOSOMA are derived according to their sensitivity analysis. The ability of MOSOMA to solve real-life problems from electromagnetics is shown in a few examples (Yagi-Uda and dielectric filters design, adaptive beam forming in time domain…).

Multi-Objective Self-Organizing Migrating Algorithm: Sensitivity on Controlling Parameters

In this paper, we investigate the sensitivity of a novel Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) on setting its control parameters. Usually, efficiency and accuracy of searching for a solution depends on the settings of a used stochastic algorithm, because multi-objective optimization problems are highly non-linear. In the paper, the sensitivity analysis is performed exploiting a large number of benchmark problems having different properties (the number of optimized parameters, the shape of a Pareto front, etc.). The quality of solutions revealed by MOSOMA is evaluated in terms of a generational distance, a spread and a hyper-volume error. Recommendations for proper settings of the algorithm are derived: These recommendations should help a user to set the algorithm for any multi-objective task without prior knowledge about the solved problem

Structure-Based Evolutionary Design Applied to Wire Antennas

A new design technique for antennas, namely the Structure-based Evolutionary Design (SED), is introduced and described in detail. SED is a new global random search method derived by the “genetic programming”, a strategy proposed by Koza. The proposed technique will be compared with the genetic algorithms (GA), a widely used design technique, showing the numerous advantages of our approach with respect to standard ones. SED assumes no “a priori” structure, but it builds up the structure of the individuals as the procedure evolves. Therefore SED is able to determine both the structure shape and dimensions as an outcome of the procedure (infinite-dimensional solution space), acting on subparts of the whole structure, and allowing to explore effectively the far more vast solution space. We thoroughly discuss both the general features of SED and its application to wire antenna design. The antenna internal representation, which is a key to the successful implementation of SED, and the construction of fitness functions from the antenna specifications will be described in detail. The proposed approach has been assessed with many different cases, using as design requirements both Gain and VSWR in a frequency band as wide as possible, and with the smallest size. The results obtained with SED are finally compared with other popular algorithms like Particle Swarm Optimization (PSO) and Differential Evolution (DE), showing that both the computational cost and the complexity are of the same order of magnitude, but the performances obtained by SED are significantly higher

Communication Subsystems for Emerging Wireless Technologies

The paper describes a multi-disciplinary design of modern communication systems. The design starts with the analysis of a system in order to define requirements on its individual components. The design exploits proper models of communication channels to adapt the systems to expected transmission conditions. Input filtering of signals both in the frequency domain and in the spatial domain is ensured by a properly designed antenna. Further signal processing (amplification and further filtering) is done by electronics circuits. Finally, signal processing techniques are applied to yield information about current properties of frequency spectrum and to distribute the transmission over free subcarrier channels

A Platform for Antenna Optimization with Numerical Electromagnetics Code Incorporated with Genetic Algorithms

This thesis investigation presents a unique incorporation of the Method of Moments (MoM) with a Genetic Algorithm (GA). A GA is used in accord with the Numerical Electromagnetics Code, Version 4 (NEC4) to create and optimize typical wire antenna designs, including single elements and arrays. Design parameters for the antenna are defined and encoded into a chromosome composed of a series of numbers. The cost function associated with the specific antenna of interest is what quantifies improvement and, eventually, optimization. This cost function is created and used by the GA to evaluate the performance of a population of antenna designs. The most successful designs of each generation are kept and altered through crossover and mutation. Through the course of generations, convergence upon a best design is attained. The Yagi-Uda and the Log Periodic Dipole Array (LPDA) antennas are the focus of this study. The objectives for each antenna are to maximize the main power gain while minimizing the Voltage Standing Wave Ratio (VSWR) and the antenna\u27s length. Results for the Yagi-Uda exceed previous designs by as much as 40 dB in the main lobe while maintaining respectable length and VSWR values. The improvements made in the LPDA antenna were not as drastic, finding a nominal increase in power gain while truncating original allowance in the length by more than half, along with nominal VSWR values that were close to the ideal value of one. The percentage of bandwidth covered for the frequencies of interest are 8.11% for the Yagi-Uda and 10.7% for the LPDA. GA performance is evaluated and, based on previous results, implemented with real-numbered chromosomes as opposed to the classic binary encoding. This methodology is very robust and is improved upon in this research, all while using a novel approach with an optimization program platform called iSIGHT, developed by Engineous Software

Yagi-Uda Antenna Gain Improvement for Enhanced Reception of DVB-T2 Signals

Yagi-Uda Antenna is a widely used roof top DVB-T2 receiver antenna due to its high forward gain capability, low cost and ease in construction. In Tanzania, there have been some complaints which were logged to Tanzania Communications Regulatory Authority (TCRA) by the customers on the poor reception of DVB-T2 signals which may be caused by signal degradation. In this paper we propose enhancement of the gain of the Yagi antenna so as to improve the reception signals of the DVB-T2. This will help solve those complaints. It is well known that the increase in radiation pattern causes the increase in directivity and hence gain which will have an impact on good quality of reception for DVB-T2 signals coming from the transmitter. After carefully design and simulation in FEKO simulating software by adding the number of director elements and making some adjustments on the length and spacing between the elements, we managed to increase the gain of the antenna by 4.7dB. This is significant improvement of the quality of received signals. Keywords: DVB-T2, Yagi Uda antenna, Set Top Box (STB), antenna gain, Directivity, Wavelength, Electric field strength, Signal reception, Radiation pattern

Software Solutions for Antenna Design Exploration: A Comparison of Packages, Tools, Techniques, and Algorithms for Various Design Challenges

Numerous software packages exist for solving antenna design optimization problems, with many of these employing a variety of approaches, leading, in turn, to variations in optimization performance. Antenna designers, often not fully schooled in optimization, can be confused as to which algorithm in which software package should be used. A wrong choice can cause the failure of the optimization or the expending of considerable time on the computationally expensive 3D electromagnetic (EM) simulations involved. While it is true that the various algorithms, combined with the variety of complex challenges found in different real-world scenarios make a direct comparison among tools difficult, a robust attempt at such an evaluation is overdue

IWO-based Synthesis of Log-Periodic Dipole Array

The Invasive Weed Optimization (IWO) is an effective evolutionary and recently developed method. Due to its better performance in comparison to other well-known optimization methods, IWO has been chosen to solve many complex non-linear problems in telecommunications and electromagnetics. In the present study, the IWO is applied to optimize the geometry of a realistic log-periodic dipole array (LPDA) that operates in the frequency range 800-3300 MHz and therefore is suitable for signal reception from several RF services. The optimization is applied under specific requirements, concerning the standing wave ratio, the forward gain, the gain flatness and the side lobe level, over a wide frequency range. The optimization variables are the lengths and the radii of the dipoles, the distances between them, and the characteristic impedance of the transmission line that connects the dipoles. The optimized LPDA seems to be superior compared to the antenna derived from the practical design procedure

Time and Frequency Domain Simulation, Measurement and Optimization of Log-Periodic Antennas

Log-periodic antenna is a special antenna type utilized with great success in many broadband applications due to its ability to achieve nearly constant gain over a wide frequency range. Such antennas are extensively used in electromagnetic compatibility measurements, spectrum monitoring and TV reception. In this study, a log-periodic dipole array is measured, simulated, and then optimized in the 470–860 MHz frequency band. Two simulations of the antenna are initially performed in time and frequency domain respectively. The comparison between these simulations is presented to ensure accurate modelling of the antenna. The practically measured realized gain is in good agreement with the simulated realized gain. The antenna is then optimized to concurrently improve voltage standing wave ratio, realized gain and front-to-back ratio. The optimization process has been implemented by using various algorithms included in CST Microwave Studio, such as Trusted Region Framework, Nelder Mead Simplex algorithm, Classic Powell and Covariance Matrix Adaptation Evolutionary Strategy. The Trusted Region Framework algorithm seems to have the best performance in adequately optimizing all predefined goals specified for the antenna