臺灣博碩士論文加值系統

本論文主要目的在於將模糊理論應用於三相感應電動機的轉速控制器設計。模糊理論的分析方法經證實適用於不易由傳統方法實現控制器設計的多變數非線性系統。本論文首先應用Mamdani模糊推論法建立初步控制規則庫，並據以產生輸出入數據資料。由於Sugeno模糊法則線性輸出的型式可對系統形成簡易且有效的描述，本論文依據此輸出入數據資料，配合適應性網路模糊推論系統，再求解出Sugeno型式的模糊法則，作為以電動機轉速誤差量及轉速誤差變化量作為輸入變數的轉速控制器之控制規則庫。該控制器並配合參數自動調整機制，以進一步改善穩態誤差。文中設計一套三相感應電動機轉速控制實驗系統，以驗證本論文提出的模糊控制器在不同操作情況下，包括無載、加載、正反轉、任意轉，確實具備對負載變動的強健性。
本文提出的模糊邏輯控制器將在幾種不同情況下作模擬與實驗，包括無載、加載、正反轉、任意轉等，實驗結果證明了模糊控制器確實具備了負載變動的強健性。

The main purpose of this thesis is to study the design of a fuzzy speed controller for the three-phase induction motor. The method of fuzzy theory is suitable for the analysis of multi-input multi-output (MIMO) nonlinear systems of which controllers are not easily implemented by classical methods. In the thesis, a preliminary set of control rules is constructed using Mamdani type of inference system and an input-output data set is generated from the preliminary set of control rules. Due to the compact and efficient form of linear representation of the Sugeno type fuzzy rules, a set of Sugeno type fuzzy control rules is then obtained from the input-output data set by employing the Adaptive Network-based Fuzzy Inference System (ANFIS). This set of Sugeno type fuzzy control rules, with the speed error and the change of speed error being input quantities, forms the speed controller for the three-phase induction motor. Moreover, the self-tuning mechanism is applied to improve the steady-state error. Through an experimental motor control system for the three-phase induction motor, the proposed fuzzy logic controller has been tested under several different operating conditions. The results illustrate that the proposed fuzzy controller has the features of robustness to load variation.

第１章 緒論1
１-１ 背景與動機1
１-２ 研究目的3
１-３ 章節概述4
第２章 模糊理論5
２-１ 模糊理論概述5
２-２ 模糊集合5
２-２-１ 隸屬函數7
２-２-２ 模糊集合的運算與性質8
２-３ 模糊蘊含與近似推理10
２-３-１ 模糊蘊含10
２-３-２ 近似推理11
２-４ 模糊邏輯控制器12
２-４-１ 模糊化15
２-４-２ 知識庫15
２-４-３ 模糊推論機17
２-４-４ 解模糊化21
２-５ 模糊與類神經網路22
第３章 模糊控制器的設計26
３-１ 前言26
３-２ 傳統模糊邏輯控制器之設計26
３-２-１ 步階響應分析26
３-２-２ 輸出入變數的訂定28
３-２-３ 控制知識庫的建立29
３-３ 適應性網路模糊推論系統36
３-４ 適應性網路模糊推論系統在控制器設計中的運用39
３-５ 因子校正模糊控制器43
３-６ 加權因子的自調整46
第４章 實驗系統與設計48
４-１ 座標轉換48
４-２ 感應馬達d-q軸數學模式49
４-３ 實驗系統架構52
４-３-１ 硬體部份52
４-３-２ 軟體部份54
４-３-３ 實驗系統55
４-３-４ 參數自調整在實驗系統中的製作57
第５章 實驗結果與分析60
５-１ Mamdani Type 與 Sugeno Type 的模糊推論法60
５-２ 實驗與結果63
５-２-１ 基本模糊型式模糊邏輯控制器64
５-２-２ 參數自調整模糊邏輯控制器74
５-２-３ 固定參數模糊邏輯控制器83
５-２-４ 參數自調整模糊邏輯控制器在其他轉速指令之應用88
第６章 結論97
６-１ 研究成果97
６-２ 未來發展方向98
參考文獻100
附錄A103

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