感應馬達向量控制系統之適應性TSK模糊估測器設計

Design of Adaptive Tskagi-Sugeno-Kang Fuzzy Estimators for Induction Motor Vector Control System.

曾揚誠(Yang-Cheng Tseng)

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(2011年)

https://doi.org/10.6841/NTUT.2011.00219

摘要

本研究設計之感應馬達控制系統是基於直接轉子磁場導向架構與適應性控制法則，並將Takagi-Sugeno-Kang (TSK)模糊系統與投影演算法植入適應性降階型T-S模糊磁通估測器，設計出轉速與定轉子電阻估測器，以Lyapunov定理來確保系統之穩定性。
本研究適應性降階型T-S模糊磁通估測器來精確估測轉子磁通，並利用LMIs方法，求出使系統穩定之估測增益，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缺點，同時減少運算時間。
經由模擬與實驗結果證明，感應馬達磁場導向控制系統植入T-S模糊磁通估測器、TSK模糊轉速估測器與定與轉子電阻估測器，在36 rpm到2000 rpm之轉速下運轉，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約在±6 rpm以內，同時所提出之估測器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

This thesis combines direct field orientation control(DFOC) and adaptivecontrol scheme in an induction motor drive.This research embedsTakagi-Sugeno-kang (TSK) Fuzzy system and projection algorithmin in the rotor speed,and the stator and rotor resistance estimators derived from adaptive pseudo-reduced-order Takagi-Sugeno (T-S) fuzzy flux estimator,and applies Lyapunov theory to ensure the stability of the system.
In addition, an adaptive pseudo-reduced-order Takagi-Sugeno (T-S) fuzzyflux observer is used to estimate the rotor flux precisely,and the estimator gain can be obtained by solving a set of linear matrix Inequalities (LMIs) for guaranteeingthe stability of the proposed flux estimation schemes, to solve the problem that the controller gains of pole assignment must follow the speed command, which oftenhappens when the adaptive full-order flux observer (AFO) is applied. Meanwhile,the computation time of control algorithm can be decreased.
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 Articulation Controller ； Vector Control

參考文獻

[9] 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。

[42] 溫曜禎，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，碩士論文，國立台北科技大學，台北，2010。

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