Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/17987
標題: 使用蘊含分解機制之PSO於共平面波饋入型單極天線阻抗之設計
CPW-fed Monopole Antenna Characterized by Using Particle Swarm Optimization Incorporating Decomposed Objective Functions
作者: 沈孟呈
Shen, Meng-Cheng
關鍵字: CPW-fed antennna;共平面波饋入型天線;particle swarm optimization;decomposed objective function;equivalent circuit;阻抗粒子尋優演算法;分解機制函數;等效電路
出版社: 應用數學系所
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摘要: 
本文嘗試一種改良的粒子群優(PSO)技巧,以之最佳化一個共平面波導饋入型(CPW-fed)單極天線饋入點的等效阻抗,藉以建立天線幾何參數與電路元件值之間關聯性,在頻寬需求下滿足其阻抗響應,使天線的設計更具系統化。與傳統PSO不同處,本文提出的改善方法為:關於目標函數的求值過程中,係經由幾個不同的權重函數將目標函數值解析,所解析出來的各個目標函數值再分別對應到粒子中指定的一個或多個因數;如此,可以解決目標函數維度不足的問題,避免粒子被過度的演化。且針對一個實際設計出來的共平面波導饋入型單極天線進行的電腦模擬,結果顯示本文用以改善粒子尋優的技巧確實可以克服上述維度不足的問題。

A systematic design strategy for Coplanar Waveguide fed (CPW-fed) monopole antennas is developed in this work by using an improved Particle Swarm Optimization (PSO) to determine the optimized values of an equivalent circuit's components. The impedance response on the desired frequency band can approximate that of the antenna at the feed point. Owing to the problems of information deficiency in the objective function, optimized results via conventional PSOs generally have failed to satisfy the expected requirements. An improved PSO incorporating a Decomposed Objective Function (PSO-DOF) is therefore proposed to overcome this problem. The objective function is first decomposed into a number of portions by using a set of weighting functions, and then each decomposed portion is used to evolve a corresponding group of factors in a particle. Because of the results optimized via the proposed PSO-DOF, the relationship between the antenna geometrical dimensions and circuit components can be established as a guideline for adjusting the antenna configuration to meet the desired specifications. Simulation results have demonstrated that the PSO-DOF is superior to the other PSO schemes in characterizing an equivalent circuit of a CPW-fed monopole antenna at the feed point, and successfully addressing the issue of information deficiency in the objective function.
URI: http://hdl.handle.net/11455/17987
其他識別: U0005-1605200808271300
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