A Neuro-Fuzzy Network for the Design of Circular and Triangular Equilateral Microstrip Antennas

A fast method for the design of circular and equilateral triangular microstrip antennas, based on a Neuro-Fuzzy Network, is presented. Numerical results obtained by using this technique agree quite well with the Moment Method results. The proposed technique can be fruitfully used in microwave and millimeter wave CAD applications.     

Annular Ring Microstrip Antennas for Millimeter Wave Applications

This work presents a fullwave analysis for annular ring microstrip antennas on uniaxial anisotropic substrates. The effect of the anisotropic substrates on the antenna performance at the millimeter wave band is investigated. The analysis is performed in the Hankel transform domain using Hertz vector potentials and Galerkin Method. Numerical results are presented for the antenna main characteristics such as resonant frequency and radiation pattern.     

Artificial Neural Networks for Resonant Frequency Calculation of Rectangular Microstrip Antennas with Thin and Thick Substrates

Neural models based on multilayered perceptrons for computing the resonant frequency of rectangular microstrip antennas with thin and thick substrates are presented. Eleven learning algorithms, Levenberg-Marquardt, conjugate gradient of Fletcher-Reeves, conjugate gradient of Powell-Beale, bayesian regularization, scaled conjugate gradient, Broyden-Fletcher-Goldfarb-Shanno, resilient backpropagation, conjugate of Polak-Ribiére, backpropagation with adaptive learning rate, one-step secant, and backpropagation with momentum, are used to train the multilayered perceptrons. The resonant frequency results obtained by using neural models are in very good agreement with the experimental results available in the literature. When the performances of neural models are compared with each other, the best result is obtained from the multilayered perceptrons trained by Levenberg-Marquardt algorithm.     

Optimization of Circular Ring Microstrip Antenna Using Genetic Algorithm

Circular ring microstrip antennas have several interesting properties that make it attractive in wireless applications. Although several analysis techniques such as cavity model, generalized transmission line model, Fourier-Hankel transform domain and the method of matched asymptotic expansion have been studied by researchers, there is no efficient design tool that has been incorporated with a suitable optimization algorithm. In this paper, the cavity model analysis along with the genetic optimization algorithm is presented for the design of circular ring microstrip antennas. The method studied here is based on the well-known cavity model and the optimization of the dimensions and feed point location of the circular ring antenna is performed via the genetic optimization algorithm, to achieve an acceptable antenna operation around a desired resonance frequency. The antennas designed by this efficient design procedure were realized experimentally, and the results are compared. In addition, these results are also compared to the results obtained by the commercial electromagnetic simulation tool, the FEM based software, HFSS by ANSOFT.     

The Method of Angular Line to Calculate Eigenvalues for Microstrip Antennas

The method of angular line (MAL) is presented for calculating the resonant frequency of microstrip antenna, which is available in other literature and originally used to analyze various waveguide structure. The results obtained by using this method are in conformity with those reported elsewhere.     

Support Vector Driven Genetic Algorithm for the Design of Circular Polarized Microstrip Antenna

In this paper, a hybrid soft computing method for designing specific microstrip antenna is presented. Evolutionary algorithm such as genetic algorithm (GA) is one of the promising ways of finding global optimum solution from a multivariate nonlinear feature space. Being a stochastic iterative algorithm, it requires much computation power when the function to be optimized is complex and time consuming. Various meta-modelling techniques such as neural network, response surface methods, kriging, etc. can be used to model the process under optimization in order to reduce the computational expenses. In this paper, we investigate one such technique – support vector regression (SVR) – to model the complex analytical process. The model, thus obtained, is used for optimization using genetic algorithms. This approach is demonstrated for the design of circular polarized microstrip antenna at 2.6 GHz band. The results of SVR model are compared with other meta-models generated with neural network and response surface methodology.     

Calculation of Magnetic Configuration and Resistance for Nanomagnets

Based on a classical Heisenberg lattice model with dipole interaction and the method of spin dynamic simulation,the magnetic configurations (MC),hysteresis loop (HL) and magnetic resistance (MR) of the nanomagnets with different geometries,such as circle,square and rectangle,are studied for different directions of applied field.In the case of perpendicular field to the plane,the magnetization and MR are reversible and have not hysteresis.When the field is applied in the plane,the HL is irreversible and is qualitatively well agreeable with the current experimental results.The MR loop is also irreversible and appears two peaks distributed at two sides around zero field.The peaks of magnetic resistance are relative to the vortex state of similar configuration.Large easy-axis anisotropy will suppress the MC anisotropy,and the large magnetoresistance effect disappears.     

太阳能光伏-热伏发电板的自适应追光系统设计与实现

在小型太阳能光伏-热伏发电系统中,为了提高其发电效率,通常会辅以自动追光系统。针对现有的基于多光电二极管的自动追光系统结构复杂等问题,提出了一种基于光敏电阻的自适应追光系统。为了实现发电板对光源的追踪,采用了基于负反馈的自适应追光原理,通过软件设计控制追光精度,同时增加了系统位置消抖控制。在硬件方面,采用光敏电阻感应光强,借助AD转换电路和舵机,以驱动太阳能光伏-热伏发电板转动直至发电板平面垂直于太阳光;优化设计了光敏电阻与板面的夹角大小以调整追光的区域及误差。最后完成了整体装置的机械结构设计和电路图设计及仿真,结果表明,与现有的多光电二极管追光系统相比,所设计的追光系统机械装置部分的设计更加简单,便于实现,同时通过优化设计改善了追光的稳定性。