感應馬達適應性磁場導向控制系統之T-S模糊估測器設計

Design of Induction Motor FOC System using Adaptive T-S Fuzzy Estimator.

溫曜禎(Yao-Chen Wen)

指導教授 ： 王順源

國立臺北科技大學/電資學院/電機工程系所/碩士(2010年)

https://doi.org/10.6841/NTUT.2010.00335

摘要

由於感應馬達在長時間運轉下，受內部溫升效應影響定、轉子電阻值會變動，造成轉子磁通估測器準確性降低。因此本研究基於直接轉子磁場導向感應馬達控制系統為基礎，設計適應性Takagi-Sugeno (T-S) 模糊降階型磁通估測器與適應性Takagi-Sugeno-Kang (TSK) 模糊定轉子電阻估測器，並將估測器植入感應馬達向量控制系統中，以精確估測轉子磁通。穩定度分析使用LMIs方法，求出使系統穩定之估測器增益，以確保磁通估測器之穩定度。本研究並利用TSK模糊估測器作轉速估測，將估測之轉速回授至適應性監督式模糊小腦模型速度控制器，以達到無轉速量測器向量控制之目的。
經由模擬與實驗結果證明，感應馬達磁場導向控制系統中，植入T-S模糊磁通估測器、TSK模糊定、轉子電阻估測器與轉速估測器，運轉在36 rpm到2000 rpm之轉速下，負載為8 Nm時轉速皆有優異的動態響應，由實驗結果可知，穩態誤差皆±6 rpm以內，同時馬達狀態估測在電阻值參數變動之環境下仍具有很好的系統強健性。

關鍵字

Takagi-Sugeno模糊估測器 ； Takagi-Sugeno-Kang模糊系統 ； 參考模型適應系統 ； 小腦模型控制器 ； 磁場導向控制

並列摘要

Generally, it is well known that the rotor flux of induction motor cannot be accurately estimated owing to the fluctuation of rotor resistance caused by temperature variation, so that this thesis proposes an adaptive pseudo reduced-order Takagi-Sugeno (T-S) fuzzy flux estimator and an adaptive Takagi-Sugeno-Kang (TSK) rotor resistance estimator for the induction motor speed drives utilizing the scheme of direct field orientation. The estimator gain can be obtained by solving a set of linear matrix inequalities (LMIs) for guaranteeing the stability of the proposed flux estimation schemes. Moreover, the thesis utilizes a Takagi-Sugeno-Kang (TSK) technique to estimate the rotor speed precisely, fed back to the adaptive supervisory fuzzy cerebellar model articulation speed controller (AFCMAC) to achieve the sensorless control.
To verify the practicality and effectiveness of the proposed schemes, experiments are performed under the conditions that the speed command varies from 36 rpm to 2000 rpm of rated speed and the 8 Nm torque load is applied from beginning to end. The experimental results indicate that the proposed system has not only superior speed dynamic response but also satisfactory robustness in the presence of parameter variations.

並列關鍵字

Takagi-Sugeno Fuzzy Flux Estimator ； Model Reference Adaptive System ； Takagi-Sugeno-Kang Fuzzy System ； Cerebellar Model ArticulationController ； Vector Control

參考文獻

[6] 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，台北：國立台北科技大學，2008。

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