臺灣博碩士論文加值系統

本論文提出永磁式同步旋轉馬達及行波式環型超音波馬達兩種致動方式截然不同的致動器之動態建模與智慧型控制方法，在永磁式同步旋轉馬達的建模與驅動部分，本文推導其精確數學模型，並利用磁場導向的控制方式結合正弦波寬調變(SPWM)策略驅動馬達，在Matlab/Simulink中建構出永磁式同步馬達的驅動系統架構；環型超音波馬達的建模與驅動方式則分別採用二維解析法及LLCC共振驅動電路來完成。
在控制方面，本文針對兩種馬達的速度控制提出一自我建構及簡化之遞迴式模糊類神經網路(Self-Constructing and Simplification Recurrent Fuzzy Neural Network)來達成追蹤週期性參考模式命令。其線上學習可分成架構學習與參數學習兩個部分，架構學習演算法是判別系統是否產生模糊規則，參數學習則是利用監督式梯度遞降法來調整神經網路之連結權重值，在系統穩定後再利用模糊決策方式使其可自動刪除不重要之模糊規則，藉此達到自建遞迴式模糊類神經網路可得到架構簡單又能有良好控制性能的目標，面對不同的受控系統時，又能依據各系統的特性而建立適合該系統的模糊規則庫，進而控制各種不同的受控場。
　　本文利用Simulink模擬兩種馬達之建模、驅動及控制三大部分的總集結果，並且與基因-模糊控制系統為基礎的驅動系統作比較，驗證所提的控制方法在面對兩種完全不同的驅動架構時，均能有良好且高精密的速度追蹤響應，遭受負載及參數變動時亦能具有優良的強健性。

This paper presents a dynamic modeling and intelligent control method for two different type actuators, the permanent magnet synchronous motor (PMSM) and the traveling wave ultrasonic motor (TWUSM). In the dynamic modeling and drive system of permanent magnet synchronous motor, the precise mathematical model has been derived by using a field-oriented control method and combination of sinusoidal pulse width modulation (SPWM) strategies, which are easily to construct the whole simulation system in the Matlab Simulink. For the dynamic modeling and drive system of traveling wave ultrasonic motor two-dimensional analytical method with LLCC resonant driving circuit are adopted.
In control aspect, this paper proposed a self-constructing and simplification recurrent fuzzy neural network for the speed control of two different motors to trace periodic reference trajectories. The proposed learning algorithm consists of structure learning and parameter learning. The structure learning determines neurons (fuzzy rules) generation, while the parameter learning algorithm used the supervised gradient decent method to adjust the connected weights in the consequent part. When the system is stable, fuzzy decision-making method is used to delete unimportant fuzzy rules automatically, so as to achieve a simplest structure of SCRFNN. Even confront with different system, the proposed method may create a suitable fuzzy rule base according to the characteristics of each system, and show a good control performance.
Finally, this article use Simulink to simulation the part of dynamic modeling, drive system and control of two kinds motors. After comparing simulation results with the drive system base on GA-Fuzzy control system, it can be verified the proposed control method in face of two completely different drives systems, still have good speed and high precision tracking response. When the system is subjected to load and parameter changes, it also exists good robustness.

中文摘要
英文摘要
誌謝
目錄
表目錄
圖目錄
第一章 緒論
1.1 研究動機與目的
1.2 論文大綱
第二章 永磁式同步旋轉馬達(PMSM)
2.1 永磁式同步旋轉馬達之基本介紹與文獻回顧
2.2 永磁式同步旋轉馬達之磁場導向控制
2.2.1 座標轉換與電壓方程式
2.2.2 功率與電磁轉矩方程式
2.2.3 馬達旋轉運動方程式
2.3 永磁式同步旋轉馬達之驅動系統
2.4 傳統永磁式同步旋轉馬達驅動系統模擬
第三章 行波式環型超音波馬達(TWUSM)
3.1 行波式環型超音波馬達之基本介紹與文獻回顧
3.2 行波式環型超音波馬達動態模型
3.2.1 壓電材料之壓電方程式
3.2.2 定子與轉子接面壓力分析
3.2.3 定子動態行為特性
3.2.4 轉子之轉速與扭矩
3.3 行波式環型超音波馬達之驅動系統
3.4 傳統行波式環型超音波馬達驅動系統模擬
第四章 最佳化理論
4.1 前言
4.2 遺傳演算法基本理論
4.2.1 編碼
4.2.2 適應函數
4.2.3 複製
4.2.4 交配
4.2.5 突變
4.2.6 遺傳演算法之探討
第五章 智慧型控制理論之設計與模擬
5.1 模糊控制理論背景
5.1.1 模糊控制基本架構
5.1.2 模糊控制器結合遺傳演算法之控制系統
5.1.3 模糊控制器結合遺傳演算法於永磁式同步馬達的速度控制
5.2 類神經網路控制理論
5.2.1 類神經網路控制系統基本架構
5.2.2 模糊類神經網路控制系統
5.3 自我建構及簡化之遞迴式模糊類神經網路控制系統
5.3.1 架構學習
5.3.2 參數學習
5.3.3 自我簡化
5.4 自我建構及簡化之遞迴式模糊類神經於永磁式同步馬達的速度控制
5.5 自我建構及簡化之遞迴式模糊類神經於行波式超音波馬達的速度控制
第六章 結論與未來研究方向
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