本文選題：異步電機 + 矢量控制　； 參考：《南京郵電大學》2015年碩士論文

【摘要】：在實際的異步電機調速系統中,安裝速度傳感器存在易受環(huán)境影響、成本增加及難以維護等缺陷,而實現無速度傳感器的轉速辨識能夠有效地克服上述缺陷。另外,優(yōu)化研究異步電機調速系統中PI(比例-積分)調節(jié)器參數,對提高系統性能具有重要的意義。為此,本文研究了異步電機矢量控制系統無速度傳感器轉速辨識以及調節(jié)器參數的優(yōu)化問題,首先采用一種基于改進反電動勢的轉速模型參考PI自適應辨識方法,實現了異步電機轉速的辨識;然后采用改進的量子免疫遺傳算法同時優(yōu)化系統中轉速調節(jié)器、勵磁電流調節(jié)器、轉矩電流調節(jié)器以及轉速辨識模塊中調節(jié)器的參數,以實現系統的優(yōu)化控制;最后,在Matlab仿真及硬件平臺,驗證了本文工作的有效性。本文主要工作如下:1、研究了異步電機無速度傳感器轉速辨識問題。首先,采用一種基于改進反電動勢的轉速模型參考PI自適應辨識方法,該方法只需檢測定子電流和定子電壓就能實現異步電機轉速的辨識,結構簡單、易于實現;然后,采用小信號分析法分析了轉速辨識子系統的穩(wěn)定性;最后,基于Matlab/Simulink仿真平臺,搭建異步電機無速度傳感器矢量控制系統并進行仿真研究,仿真結果表明:采用基于改進反電動勢的轉速模型參考PI自適應辨識方法所估計的轉速能準確有效地跟蹤實際的轉速。2、進一步研究了異步電機無速度傳感器矢量控制系統的優(yōu)化控制問題。首先,設計了包含系統轉速輸出跟蹤誤差以及調節(jié)器輸出約束的多性能指標函數,并采用改進的量子免疫遺傳算法同時整定異步電機無速度傳感器矢量系統中轉速調節(jié)器、勵磁電流調節(jié)器、轉矩電流調節(jié)器以及轉速辨識模塊中調節(jié)器的參數,以實現系統的優(yōu)化控制;然后,采用Matlab仿真工具,完成異步電機無速度傳感器矢量控制系統的優(yōu)化仿真;最后,基于求是教儀平臺,進行實驗驗證。實驗結果表明:采用改進量子免疫遺傳算法的優(yōu)化結果能使調速系統具有良好的性能。
[Abstract]:In the actual speed regulation system of asynchronous motor, the installed speed sensor is easy to be affected by the environment, the cost is increased and it is difficult to maintain, but the speed identification without speed sensor can effectively overcome the above defects. In addition, it is of great significance to optimize the PI- (proportional-integral) regulator parameters in the asynchronous motor speed regulation system. In this paper, the speed identification without speed sensor and the optimization of regulator parameters in vector control system of asynchronous motor are studied in this paper. Firstly, a speed model reference Pi adaptive identification method based on improved backEMF is adopted. The speed identification of asynchronous motor is realized, and the parameters of speed regulator, excitation current regulator, torque current regulator and speed identification module are optimized by using the improved quantum immune genetic algorithm. Finally, in Matlab simulation and hardware platform, the effectiveness of the work is verified. The main work of this paper is as follows: 1. The speed identification problem of asynchronous motor without speed sensor is studied. Firstly, a speed model reference Pi adaptive identification method based on improved backEMF is adopted. This method can identify the speed of asynchronous motor only by detecting stator current and stator voltage, which is simple and easy to realize. The stability of speed identification subsystem is analyzed by small signal analysis method. Finally, based on Matlab/Simulink simulation platform, the speed sensorless vector control system of asynchronous motor is built and simulated. The simulation results show that the speed estimation based on the improved backEMF model reference Pi adaptive identification method can track the actual speed accurately and effectively. Furthermore, the speed sensorless vector of asynchronous motor is studied. Optimal control problem of control system. Firstly, a multi-performance index function including system speed output tracking error and regulator output constraints is designed, and an improved quantum immune genetic algorithm is used to adjust the speed regulator in the speed sensorless vector system of asynchronous motor simultaneously. The parameters of excitation current regulator, torque current regulator and speed identification module are used to realize the optimal control of the system. Then, the optimal simulation of speed sensorless vector control system of asynchronous motor is completed by using Matlab simulation tool. Finally, based on the platform of Qiushi teaching instrument, experimental verification is carried out. The experimental results show that the improved quantum immune genetic algorithm can make the speed regulation system have good performance.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM343

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本文編號：1881192