本文選題：NSGA-II　切入點：多目標(biāo)粒子群優(yōu)化　出處：《電子科技大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：在實際應(yīng)用中,大多數(shù)科學(xué)和工程問題都是多目標(biāo)優(yōu)化問題,由于各個目標(biāo)函數(shù)之間有可能是不可折衷或者相互沖突的,因此不可能有唯一確定的解,能夠使所有的目標(biāo)同時達(dá)到最優(yōu),對于這些問題通常優(yōu)化得到的都是一個非支配(Pareto)最優(yōu)解集。作為最適應(yīng)可重構(gòu)特性的天線結(jié)構(gòu)之一,可重構(gòu)像素天線(reconfigurable pixel antenna)一般由若干個電小的金屬貼片陣列構(gòu)成,貼片之間通過RF開關(guān)彼此連接,通過改變開關(guān)的通斷狀態(tài),能夠靈活地構(gòu)造多種天線形狀,從而更易實現(xiàn)天線的可重構(gòu)性能。但是,由于加載的開關(guān)數(shù)量較多,可重構(gòu)像素天線的設(shè)計較為復(fù)雜,所以必須借助高效的搜索方法來挖掘天線潛在的重構(gòu)能力。本文主要針對多目標(biāo)智能優(yōu)化算法和可重構(gòu)像素天線進(jìn)行了若干相關(guān)研究,具體工作內(nèi)容如下:1.提出了一種自適應(yīng)的帶有精英保留策略的快速非支配遺傳算法(self-adaptive NSGA-II),通過不同特性的基準(zhǔn)測試函數(shù)與傳統(tǒng)的帶有精英保留策略的快速非支配遺傳算法(NSGA-II)和多目標(biāo)粒子群優(yōu)化算法(MOPSO)進(jìn)行對比,使用收斂性度量和分布性度量指標(biāo)對優(yōu)化結(jié)果進(jìn)行評估,進(jìn)而證明self-adaptive NSGA-II的高效性。2.使用提出的self-adaptive NSGA-II對一款方向圖可重構(gòu)像素天線進(jìn)行優(yōu)化,并與微遺傳算法(MGA)的優(yōu)化結(jié)果進(jìn)行對比,結(jié)果表明多目標(biāo)智能優(yōu)化算法在天線設(shè)計優(yōu)化中較單目標(biāo)智能優(yōu)化算法具有更大的優(yōu)勢。3.在可重構(gòu)像素天線中,距饋電端口距離不等的開關(guān)通斷對天線性能的影響不同。為了均衡遠(yuǎn)近開關(guān)對天線可重構(gòu)的影響,同時減少開關(guān)數(shù)量,降低天線的復(fù)雜性,提出一款非均勻尺寸像素單元的可重構(gòu)像素天線,并使用self-adaptive NSGA-II對天線開關(guān)狀態(tài)進(jìn)行優(yōu)化,使天線在兩個工作頻率下分別實現(xiàn)六個方向的方向圖可重構(gòu)性能。
[Abstract]:In practical applications, most scientific and engineering problems are multi-objective optimization problems. All the targets can be optimized at the same time. For these problems, the optimal solution set is a non-dominated Pareto optimal solution set, which is one of the most suitable antenna structures for reconfigurable properties. Reconfigurable pixel antenna is generally composed of several small metal patch arrays, which are connected to each other by RF switches and can be flexibly constructed by changing the on-off state of the switches. Therefore, it is easier to realize the reconfigurable performance of the antenna. However, the design of the reconfigurable pixel antenna is more complicated because of the large number of loaded switches. Therefore, it is necessary to mine the potential reconstruction ability of antenna by efficient search method. In this paper, we mainly focus on multi-objective intelligent optimization algorithm and reconfigurable pixel antenna. The main work is as follows: 1. An adaptive fast non-dominated genetic algorithm with elitist retention strategy is proposed, which is self-adaptive NSGA-IIA. By using the benchmark function with different characteristics and the traditional fast non-dominance with elitist retention strategy, this paper proposes an adaptive fast non-dominated genetic algorithm with elitist reservation strategy. The transmission algorithm NSGA-II) and the multi-objective particle swarm optimization algorithm (MOPSO) are compared. The convergence metric and distribution metric are used to evaluate the optimization results, and the efficiency of self-adaptive NSGA-II is proved. 2.Using the proposed self-adaptive NSGA-II to optimize a pattern reconfigurable pixel antenna, Compared with the optimization results of microgenetic algorithm (MGA), the results show that the multi-objective intelligent optimization algorithm has more advantages than the single-objective intelligent optimization algorithm in antenna design optimization. In order to balance the effect of the distance between the far and near switches on the antenna reconfiguration, reduce the number of switches and reduce the complexity of the antenna, the switch with different distance from the feed port has different effects on the antenna performance. A reconfigurable pixel antenna with non-uniform size pixel unit is proposed, and the switching state of the antenna is optimized by using self-adaptive NSGA-II. The reconfigurable performance of the antenna can be realized in six directions at two operating frequencies.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN820;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 肖紹球,王秉中;基于微遺傳算法的微帶可重構(gòu)天線設(shè)計[J];電子科技大學(xué)學(xué)報;2004年02期

，

本文編號：1646569