摘要
基因演算法(Genetic Algorithms)是一種根據自然演化現象而發展出來的最佳化(optimization)工具。根據達爾文的物競天擇說,物種越能適應環境則生存的機會越高, 其基本精神在於仿效生物界中「物競天擇，適者生存」的自然演化法則。不像一般傳統的逼近,基因演算法是沒有數學公式。它是使用分離族群的概念來說明實際工程上最佳化的問題解[7]。本文使用MATLAB和SIMULINK語言,它是同時具有高效率的數值計算和視覺化的專業計算軟體。MATLAB和SIMULINK整合了數值分析、矩陣計算、訊號處理、繪圖物件等都將非常容易的使用,不像一般傳統的程式。其中還有各種不同的工具盒(Toolboxes)準備了先前定義好的功能以備模擬各式各樣的類型。基因演算法是設計PID控制器中最有效率的工具並不像一般傳統[8], 它的目標就是要適應在真實世界中遍布的不精準。軟計的設計指南是要開發出能容忍不確定性、部份真實執行的親和性、強健性、低解答成本的真實性。最後它的設計也被證實將會很有效率的應用在工業界。
並列摘要
Genetic Algorithms (GA) as a tool for a search and optimization methodology has now reached a mature stage. The GA works on the Darwinian principle of natural selection for which the noted English philosopher coined the phrase ”Survival of the fittest”. GA is not mathematically oriented. Unlike some traditional approaches the idea of using a population of solution to solve practical engineering optimization problems [7]. In this text, MATLAB and SIMULINK are used a technical computing environment for high-performance numerical computation and visualization. MATLAB and SIMULINK integrate numerical analysis, matrix computation, signal processing, and graphics in an easy-to-use environment without tradition programming. The several toolboxes provide many predefined function that can be called by the user to simulate various types, respectively. Genetic Algorithms has emerged as a powerful tool PID controller. That unlike the traditional is aimed at an accommodation with the pervasive imprecision of the real world [8]. Thus, the guiding principle is to exploit the tolerance for uncertainty, partial truth to achieve tractability, robustness, and low solution cost with reality. In the final, the role design has proven to be effective in practical industrial design.