本文選題：無軸承永磁同步電機(jī) + 轉(zhuǎn)子初始位置辨識(shí)�。� 參考：《華南理工大學(xué)》2014年博士論文

【摘要】：無軸承永磁同步電機(jī)（Bearingless Permanent Magnet Synchronous Motor(BPMSM)）是一種新型的集旋轉(zhuǎn)與轉(zhuǎn)子自懸浮功能于一體的電機(jī)。具有無摩擦、無磨損、不需潤(rùn)滑和密封、精度高、維護(hù)小，成本低等優(yōu)點(diǎn)，且不需激磁電流，因此在化學(xué)泵、蝸輪分子泵、血泵、高速磨粉機(jī)、壓縮機(jī)及高速飛輪等設(shè)備廣泛應(yīng)用。與普通永磁同步電機(jī)相比，BPMSM穩(wěn)定運(yùn)行時(shí)轉(zhuǎn)子處于自懸浮狀態(tài)，外界擾動(dòng)、參數(shù)攝動(dòng)等因素使轉(zhuǎn)子位置、速度及徑向位移更容易產(chǎn)生振動(dòng)和突變。本文圍繞BPMSM懸浮力產(chǎn)生機(jī)理對(duì)BPMSM數(shù)學(xué)模型、非線性解耦控制，無位置傳感運(yùn)行進(jìn)行了深入的理論分析與試驗(yàn)研究。 以面貼式四極轉(zhuǎn)矩繞組和二極懸浮繞組BPMSM為例，從麥克斯韋張量法出發(fā)，對(duì)懸浮力產(chǎn)生機(jī)理進(jìn)行深入分析，考慮永磁體、轉(zhuǎn)矩繞組、懸浮繞組和轉(zhuǎn)子偏心等因素，分析和建立了懸浮力數(shù)學(xué)模型及電磁轉(zhuǎn)矩?cái)?shù)學(xué)模型，同時(shí)從轉(zhuǎn)子動(dòng)力學(xué)出發(fā)，建立轉(zhuǎn)子運(yùn)動(dòng)方程及系統(tǒng)運(yùn)動(dòng)方程。 研究了基于轉(zhuǎn)子磁場(chǎng)定向控制的非線性解耦，控制系統(tǒng)采用PID控制懸浮繞組的徑向懸浮力，采用PI控制轉(zhuǎn)速，但在負(fù)載擾動(dòng)的時(shí)候動(dòng)態(tài)性能差，因此首次將分?jǐn)?shù)階PIλ控制器應(yīng)用到BPMSM控制中，分?jǐn)?shù)階控制器具有很多整數(shù)階系統(tǒng)無法實(shí)現(xiàn)的優(yōu)越性，仿真實(shí)驗(yàn)表明采用分?jǐn)?shù)階PIλ控制器的BPMSM控制系統(tǒng)比采用整數(shù)階PI控制BPMSM控制系統(tǒng)具有更快的響應(yīng)速度、更好的抗干擾性能，魯棒性好。 為了解決系統(tǒng)在系統(tǒng)參數(shù)和擾動(dòng)變化產(chǎn)生的抖振問題，將智能控制和分?jǐn)?shù)階結(jié)合起來，，設(shè)計(jì)了基于神經(jīng)網(wǎng)絡(luò)的分?jǐn)?shù)階滑�？刂破�，控制懸浮繞組的徑向懸浮力，以減少抖振的發(fā)生。仿真和實(shí)驗(yàn)結(jié)果說明了神經(jīng)網(wǎng)絡(luò)分?jǐn)?shù)階滑模控制系統(tǒng)不但能削減抖震，而且能達(dá)到較高的綜合控制性能。研究結(jié)果為智能分?jǐn)?shù)階控制器在BPMSM懸浮控制系統(tǒng)中的應(yīng)用提供了理論依據(jù)，為進(jìn)一步開展BPMSM高速運(yùn)行穩(wěn)定懸浮奠定基礎(chǔ)。 針對(duì)BPMSM無位置傳感器運(yùn)行的要求，提出了基于滑模觀測(cè)器的BPMSM無傳感器運(yùn)行控制研究并通過實(shí)驗(yàn)驗(yàn)證BPMSM無位置傳感器運(yùn)行。 最后歸納了本文的研究成果和創(chuàng)新工作，并對(duì)進(jìn)一步的研究提出了建議。
[Abstract]:Bearingless Permanent Magnet Synchronous Motor (BPMS MMC) is a new type of motor with the function of rotation and rotor self-suspension. With no friction, no wear, no lubrication and sealing, high accuracy, small maintenance, low cost, and no magnetic current, so in chemical pump, worm wheel molecular pump, blood pump, high speed grinding machine, Compressor and high-speed flywheel and other equipment widely used. Compared with ordinary permanent magnet synchronous motor (PMSM), the rotor is in self-suspension state when BPMSM is running stably, and the external disturbance and parameter perturbation make the rotor position, speed and radial displacement more prone to vibration and sudden change. In this paper, the mathematical model of BPMSM, nonlinear decoupling control and sensorless operation of BPMSM are studied theoretically and experimentally around the mechanism of BPMSM suspension force generation. Taking the surface mount quadrupole torque winding and the two-pole suspension winding BPMSM as examples, starting from Maxwell Zhang Liang's method, the mechanism of levitation force is deeply analyzed, and the factors such as permanent magnet, torque winding, suspension winding and rotor eccentricity are considered. The suspension force mathematical model and the electromagnetic torque mathematical model are analyzed and established. At the same time, the rotor motion equation and the system motion equation are established according to the rotor dynamics. The nonlinear decoupling based on rotor flux oriented control is studied. The control system uses PID to control the radial levitation force of the suspension winding and Pi to control the rotational speed, but the dynamic performance is poor when the load is disturbed. Therefore, the fractional Pi 位 controller is applied to BPMSM control for the first time. The fractional order controller has many advantages that can not be realized by integer order system. The simulation results show that the BPMSM control system with fractional Pi 位 controller has faster response speed, better anti-jamming performance and better robustness than the integer Pi control BPMSM control system. In order to solve the buffeting problem caused by the variation of system parameters and disturbances, a fractional sliding mode controller based on neural network is designed to control the radial levitation force of suspension windings by combining intelligent control with fractional order. To reduce the occurrence of buffeting. Simulation and experimental results show that the neural network fractional sliding mode control system can not only reduce shaking, but also achieve a higher comprehensive control performance. The results provide a theoretical basis for the application of intelligent fractional-order controller in BPMSM suspension control system, and lay a foundation for the further development of high-speed and stable suspension of BPMSM. In order to meet the requirements of BPMSM sensorless operation, a sliding mode observer based BPMSM sensorless operation control is proposed. The experimental results show that the BPMSM sensorless operation is sensorless. Finally, this paper summarizes the research results and innovative work, and puts forward suggestions for further research.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM341

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王鳳翔,鄭柒拾,王寶國(guó);不同轉(zhuǎn)子結(jié)構(gòu)無軸承電動(dòng)機(jī)的磁懸浮力分析與計(jì)算[J];電工技術(shù)學(xué)報(bào);2002年05期

2 鄧智泉,張宏全,王曉琳,嚴(yán)仰光;基于氣隙磁場(chǎng)定向的無軸承異步電機(jī)非線性解耦控制[J];電工技術(shù)學(xué)報(bào);2002年06期

3 楊國(guó)福;郭芙軍;;感應(yīng)型無軸承電動(dòng)機(jī)的模糊神經(jīng)網(wǎng)絡(luò)控制系統(tǒng)[J];電氣應(yīng)用;2006年12期

4 蔡國(guó)洋;黃守道;;無軸承異步電機(jī)氣隙磁場(chǎng)辨識(shí)方法與應(yīng)用[J];電機(jī)與控制學(xué)報(bào);2007年02期

5 年珩;賀益康;;永磁型無軸承電機(jī)控制系統(tǒng)研究[J];電力電子技術(shù);2007年02期

6 孟令孔;鄧智泉;王曉琳;仇志堅(jiān);;無軸承永磁同步電機(jī)懸浮子系統(tǒng)H_2/H_∞混合控制[J];電氣傳動(dòng);2007年02期

7 張建生;張鋼;汪希平;;無軸承電機(jī)中磁浮系統(tǒng)的互補(bǔ)PWM控制器研究[J];電子工程師;2005年12期

8 張宏荃,鄧智泉,王曉琳,嚴(yán)仰光;無軸承異步電動(dòng)機(jī)的系統(tǒng)實(shí)現(xiàn)[J];哈爾濱工業(yè)大學(xué)學(xué)報(bào);2004年11期

9 黃守道;蔡國(guó)洋;高劍;;無軸承異步電機(jī)的定子磁場(chǎng)定向解耦控制[J];湖南大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年05期

10 鄧智泉,何禮高,嚴(yán)仰光;無軸承交流電機(jī)的原理及應(yīng)用[J];機(jī)械科學(xué)與技術(shù);2002年05期

相關(guān)博士學(xué)位論文 前5條

1 孫曉東;無軸承永磁同步電機(jī)及其非線性控制研究[D];江蘇大學(xué);2011年

2 劉羨飛;磁懸浮開關(guān)磁阻電機(jī)基本參數(shù)與控制方法的研究[D];江蘇大學(xué);2008年

3 嚴(yán)欣平;無軸承永磁同步電機(jī)電磁設(shè)計(jì)與控制策略研究[D];重慶大學(xué);2008年

4 張碧陶;智能分?jǐn)?shù)階滑�？刂萍跋到y(tǒng)參數(shù)整定方法的研究[D];華南理工大學(xué);2012年

5 王瑞萍;基于分?jǐn)?shù)階控制器的永磁同步電動(dòng)機(jī)速度控制研究[D];華南理工大學(xué);2012年

本文編號(hào)：1783625