本論文主要是結合模糊理論、基因演算法及PID控制之觀念與優點有效率地設計出好的控制系統，研究如何應用基因演算法來設計一個本身具有權重調諧的模糊控制器，並與PID控制器結合應用。 我們所提出的主要的方法是藉著修改模糊邏輯控制器之三角形的歸屬函數值來達到權重調整的目的，模糊控制器內部調整權重後的輸出並與結合比例、積分與微分控制器來控制受控體，其作用主要是加快系統的響應時間。整個控制器能在受控系統的參數與特性所知有限下做穩定的控制，同時有效地改善上升時間及安定時間，更降低了最大超越量，使控制效能達到預期。 修改三角形歸屬函數後之模糊邏輯控制器並與傳統之模糊邏輯控制器做一性能比較，如上升時間,最大超越量,和積分誤差等，以實現該控制器之效能。最後列舉一些數學例子以及一個實際系統之三相感應馬達的例子經由電腦模擬的結果與數據證明，在性能上已經可以達到滿意的控制結果，顯現出我們所提出之方法的優點。 本控制器參數皆是利用基因演算法自動搜尋所得，並依性能指標的高低來調整控制器的參數。本論文所使用之演算法在實驗中展現其優點有如下四點： (1)有系統的搜尋最佳解。 (2)比傳統嘗試錯誤法節省大量搜尋時間跟精力。 (3)不需有關受控系統之專業知識及經驗。 (4)系統性能規格可由設計適當之適合函數（Fitness Function）而得。 This thesis investigates the technique of the modifications of triangular membership functions for performance improvement of fuzzy systems by means of genetic algorithms. First, we propose a simple method to modify the traditional triangular membership functions. It can to tune the membership function of error by modify method. Then, output of the fuzzy controller is transmitted into a PID controller to control plant. The controllers can stabilize a process with a minimal amount of prior knowledge and improve rise time, settling time and maximum overshoot effectively. Some illustrative examples demonstrate that satisfactory performance is achieved. Simulation results show that a better performance is obtained, when modified membership functions are utilized. By means of genetic algorithms, the parameters of the aforementioned controllers are determined to have a better performance. These experiment results show technique’s power and its advantages: 1. Systematic search. 2. This technique can save much more time and effort than that of conventional trial-and-error design method. 3. This technique does not need extra professional knowledge or mathematical analysis about system dynamics. 4. The performance specifications can be achieved by means of designing a proper fitness function.
