使用Takagi-Sugeno-Kang模糊轉速估測器之感應馬達向量控制設計

Vector Control Design for Induction Motors Using Takagi-Sugeno-Kang Fuzzy Speed Estimator

邱俊榮(Chun-Jung Chiu)

指導教授 ： 王順源

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2009年)

摘要

本研究將Takagi-Sugeno-Kang (TSK) 模糊系統植入轉速與轉子電阻估測器中，設計出TSK模糊轉速、轉子電阻估測器來達到無轉速量測器控制，並且利用適應性理論之投影演算法 (Projection Algorithm)來修正TSK模糊規則後件部的參數，所估測之轉速及轉子電阻可回授至適應性監督式模糊小腦模型轉速控制器及虛擬降階型磁通估測器以達成適應性向量控制。
本文之感應馬達向量控制系統結合直接轉子磁場導向與適應性控制法則，且採用適應性虛擬降階型磁通估測器以精確估測轉子磁通，不但解決了全階型磁通估測器置根比例常數須隨轉速命令變動而調整之缺點，同時可減少運算時間。
經由模擬與實驗結果證明，適應性監督式模糊小腦模型轉速控制器與TSK模糊轉速、轉子電阻估測器於感應馬達向量控制系統中，運轉在2%到100%之額定轉速，負載為8Nm條件下轉速響應極為優異，同時在馬達參數變動之環境下仍保持良好的強健性。

關鍵字

Takagi-Sugeno-Kang模糊系統 ； 投影演算法 ； 適應性理論

並列摘要

In this thesis, the Takagi-Sugeno-Kang fuzzy theory is used to design the TSK fuzzy speed estimator and TSK fuzzy rotor resistance estimator for establishing the speed sensor-less control. Moreover, the projection algorithm in adaptive theory is adopted to modify the parameters of the TSK fuzzy rules in the consequence part. The speed and rotor resistance estimated by the proposed estimator are fed back to the adaptive fuzzy cerebellar model articulation controller (AFCMAC) and pseudoreduced-order flux observer (APRO) in order to achieve the adaptive vector control.
The proposed vector control of the motor drive integrates the direct field orientation control (DFOC) and the adaptive control law. Also, an adaptive pseudoreduced-order flux observer (APRO) is used to estimate the rotor flux and solve the problem that the constants of pole assignment must be changed according the speed command; this problem often happens when the adaptive full-order flux observer (AFO) is applied. In addition, the use of APRO reduces the computation time of control algorithm.
Under the operation conditions that the speed range varies from 2% to 100% of the rated speed with 8-Nm start-up torque load, the experimental results indicate that the speed not only has superior dynamic response but also remains robustness in the environment of motor parameter variations when the AFCMAC, TSK fuzzy speed estimator, and TSK fuzzy rotor resistance estimators are applied.

並列關鍵字

Takagi-Sugeno-Kang Fuzzy System ； Projection Algorithm ； Adaptive Theory

參考文獻

[33] 孫敏男，適應性模糊小腦模型控制器於高性能向量控制系統之設計，碩士論文，國立台北科技大學，台北，2008。

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