由於永磁式同步馬達具有體積小、高氣隙磁通密度和高扭力的優點，所以在近來馬達控制領域中之重要性日益增加。在諸多控制方法中，向量控制是最常用的方法之一。而在實際應用上仍需考慮某些影響馬達輸出性能的因素，譬如馬達本身參數的變動、外界環境的干擾以及為簡化模型所忽略的高頻特性等等。為使所設計的系統具有強健性能，本研究中所採用的控制器是依據一個最近才被提出的二維自由度的控制架構來設計，此一控制器架構的優點是它可同時克服因馬達和控制器的參數變動而對輸出性能所造成的影響。

我們應用線性代數和 控制這兩種不同的設計方式來求得滿足設計規格的控制器。在使用線性代數的設計過程中，我們強調了internal model 對於整個系統的影響；而應用 控制設計的優點，則是在設計的過程可一併考慮時域和頻域的規格。最後經由電腦模擬的結果來說明我們設計的優點。

Because of several advantages, e.g. compact structure, high air-gap flux density, and high torque capability, the PM synchronous motor plays an important role in recent years. The basic principle of controlling a PMSM is based on vector control. The control performance is influenced by factors as the plant parameter variations, the external load disturbances, and the unmodeled or nonlinear dynamics. In the thesis, we apply a recently proposed robust 2DOF configuration to designing controllers for PMSM to achieve the robust asymptotical tracking under perturbations in both the motor and the controllers.

Two design methods are adopted to implement the desired controllers, i.e. the linear algebraic method and the design method. The effect of the well-known internal model principle is addressed in the former design method. The merit of the latter design method is that both time and frequency domain design specifications can be easily included in the design procedure. Computer simulation results are displayed to illustrate the advantages of our designs.

Abstract

List of Figures

1Introduction
1.1 Literature Review and Motivation
1.2 Mathematical Model of The PMSM and
VectorControl
1.3 Outline of the Thesis

2 Two-Degree-of Freedom Controller
2.1 Conventional Two-Degree-of-Freedom
Configuration
2.2 Robust Two-Degree-of-Freedom
Configuration
3 Linear Algebraic Design
3.1 Conventional Two-Degree-of-Freedom
Configuration
3.2 Robust Two-Degree-of-Freedom
Configuration

4 Robust Control Design Introduction
4.1 Introduction
4.2 Robust Control of Model Matching Problem
with 2DOF Configuration

4.3 Robust Control of Model Matching Problem
with Robust 2DOF Configuration

5 Design and Simulation Results
5.1 System Response of Different Control
Structures
5.2 Sensitivity Function Analysis
5.3 Weighting Function Selection and Model
Reduction

6 Conclusions

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