應用粒子群演算法於APDL模型之參數最佳化

Optimization of system parameters for APDL models Using Particle Swarm Optimization

施克隆(Ke-Lung Shih)

指導教授 ： 林志哲

國立臺北科技大學/機電學院/自動化科技研究所/碩士(2013年)

https://doi.org/10.6841/NTUT.2013.00141

摘要

本研究是利用MATLAB執行粒子群演算法(Particle Swarm Optimization, PSO)並結合有限元素分析軟體(ANSYS Parametric Design Language, APDL)求得模型之參數最佳化。
研究過程中分別以使用電流變液（Electro-Rheological Fluid, ERF）作為智慧型材料之複合式結構懸臂樑減振器與手持裝置之電池連接器端子做為案例。並在不同案例中探討不同參數搜尋的狀況下，所得到的目標函數。
同時也利用MATLAB執行基因演算法(Genetic Algorithm, GA)與利用ANSYS Workbench多目標遺傳演算法(Multi-Objective Genetic Algorithm, MOGA)來進行比對，除了呈現三種方法的最佳化結果之外，同時也比對這三種方法在搜尋時所花費的時間。

關鍵字

最佳化設計 ； 有限元素法 ； 粒子群演算法 ； 基因演算法 ； 多目標遺傳演算法 ； 電流變液

並列摘要

In this study, the optimization code using MATLAB and ANSYS parametric design language (APDL) is proposed for parameter optimization. Three type optimization methods, which are genetic algorithm(GA), particle swarm optimization(PSO) and multi-objective genetic algorithms (MOGA), are studied in three case studies. The first two optimization methods are preformed using MATLAB codes integrated with APDL simulation to obtain the optimal parameters for comparison. The last one (MOGA) is implemented using the ANSYS workbench.
The first case is to obtain the optimal frequency variation for an ERF (Electro-Rheological Fluid) embedded structure for the shock absorber. A connector design is studied for the last two cases to achieve the maximal contact force with the minimal stress.

並列關鍵字

Optimal design ； Finite element method ； Particle swarm optimization ； Genetic algorithm ； Multi-objective genetic algorithms ； Electro-Rheological Fluid

參考文獻

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