本文選題：永磁同步電機(jī) + 參數(shù)辨識(shí)　； 參考：《江南大學(xué)》2017年碩士論文

【摘要】：永磁同步電機(jī)(permanent magnet synchronous motor,PMSM)具有結(jié)構(gòu)簡(jiǎn)單、性能可靠、轉(zhuǎn)速范圍寬等優(yōu)點(diǎn)。此外,隨著永磁材料成本的持續(xù)降低,控制技術(shù)的不斷改進(jìn)和DSP等微處理器的飛速發(fā)展,永磁同步電機(jī)在智能制造、工業(yè)自動(dòng)化等高性能伺服控制領(lǐng)域得到廣泛應(yīng)用。然而永磁同步電機(jī)是一個(gè)高階耦合的非線性系統(tǒng),電機(jī)定子電阻、電感等參數(shù)容易受到溫升、磁飽和等因素影響,導(dǎo)致電機(jī)可靠性和控制性能的降低。另一方面,PMSM可靠的位置和速度信息是永磁同步電機(jī)能夠?qū)崿F(xiàn)高性能控制的關(guān)鍵。傳統(tǒng)方法是通過(guò)增設(shè)硬件傳感器來(lái)獲取這些參數(shù),但由于成本以及維護(hù)等因素制約其在永磁同步電機(jī)上的應(yīng)用。因此,參數(shù)辨識(shí)和無(wú)傳感器控制成為電機(jī)研究領(lǐng)域的熱點(diǎn)。論文主要工作如下:1.給出了永磁同步電機(jī)的數(shù)學(xué)模型,并就參數(shù)辨識(shí)和無(wú)傳感器控制的一些方法做了對(duì)比。接著簡(jiǎn)要闡述了矢量控制技術(shù),選擇了0di=的解耦方式,同時(shí)針對(duì)電氣參數(shù)對(duì)系統(tǒng)解耦以及轉(zhuǎn)速估算等電機(jī)控制性能的影響進(jìn)行了分析,說(shuō)明了進(jìn)行PMSM參數(shù)辨識(shí)的重要性。2.針對(duì)教與學(xué)優(yōu)化算法在求解復(fù)雜優(yōu)化問(wèn)題存在陷入局部解和收斂精度低等不足,提出了一種改進(jìn)教與學(xué)優(yōu)化算法對(duì)永磁同步電機(jī)進(jìn)行參數(shù)辨識(shí)。該算法在教學(xué)階段引入輔導(dǎo)教學(xué)機(jī)制加強(qiáng)教師的教學(xué)能力,提高算法收斂速度,在學(xué)習(xí)階段,采用科目分步學(xué)習(xí)提高學(xué)員學(xué)習(xí)效率,并融入反向?qū)W習(xí)策略進(jìn)行小概率變異來(lái)增加算法跳出局部最優(yōu)的可能性�；诨鶞�(zhǔn)測(cè)試函數(shù)進(jìn)行性能測(cè)試,驗(yàn)證了上述分析的正確性。通過(guò)MATLAB/Simulink仿真表明,此算法能夠有效辨識(shí)出PMSM電氣參數(shù),具有較好的收斂性和可靠性。3.考慮滑模結(jié)構(gòu)的抖振現(xiàn)象,從數(shù)學(xué)角度論證了滑�？刂频亩墩癞a(chǎn)生機(jī)制,在此基礎(chǔ)上結(jié)合靜止坐標(biāo)系下PMSM數(shù)學(xué)模型,設(shè)計(jì)了一種改進(jìn)滑模觀測(cè)器,來(lái)對(duì)其轉(zhuǎn)速和位置進(jìn)行觀測(cè)。針對(duì)高頻抖振帶來(lái)的系統(tǒng)穩(wěn)定性問(wèn)題,該觀測(cè)器引入分段式雙曲正切函數(shù)作為切換函數(shù)和可變滑模增益,以此減弱抖振�？紤]到參數(shù)不確定性對(duì)觀測(cè)精度影響,在觀測(cè)過(guò)程中引入定子阻值估算環(huán)節(jié),實(shí)時(shí)修正觀測(cè)器參數(shù),進(jìn)一步提高觀測(cè)精度。同時(shí)采用分?jǐn)?shù)階鎖相環(huán)估算出轉(zhuǎn)子位置和速度信息,從而有效避免了因傳統(tǒng)相位補(bǔ)償帶來(lái)的計(jì)算復(fù)雜性。通過(guò)在MATLAB/Simulink環(huán)境中對(duì)不同工況下轉(zhuǎn)速、位置進(jìn)行仿真,驗(yàn)證了改進(jìn)滑膜觀測(cè)器的有效性。
[Abstract]:Permanent magnet synchronous motor (PMSM) has the advantages of simple structure, reliable performance and wide speed range. In addition, with the continuous reduction of the cost of permanent magnet materials, the continuous improvement of control technology and the rapid development of microprocessors such as DSP, PMSM has been widely used in the fields of intelligent manufacturing, industrial automation and other high-performance servo control fields. However, permanent magnet synchronous motor (PMSM) is a high order coupled nonlinear system. The stator resistance and inductance of PMSM are easily affected by temperature rise and magnetic saturation, which leads to the deterioration of reliability and control performance of PMSM. On the other hand, the reliable position and speed information of PMSM is the key for PMSM to achieve high performance control. The traditional method is to obtain these parameters by adding hardware sensors, but its application in PMSM is restricted by cost and maintenance. Therefore, parameter identification and sensorless control have become a hot spot in the field of motor research. The main work of this paper is as follows: 1. The mathematical model of permanent magnet synchronous motor (PMSM) is given, and some methods of parameter identification and sensorless control are compared. Then the vector control technology is briefly described, and the decoupling mode of 0di= is chosen. At the same time, the influence of electrical parameters on the control performance of system decoupling and speed estimation is analyzed, and the importance of PMSM parameter identification is explained. Aiming at the shortcomings of teaching and learning optimization algorithm in solving complex optimization problems, such as local solution and low convergence accuracy, an improved teaching and learning optimization algorithm is proposed to identify the parameters of permanent magnet synchronous motor (PMSM). The algorithm introduces guidance teaching mechanism to strengthen the teachers' teaching ability and improve the convergence speed of the algorithm. In the learning stage, the subjects are used step by step to improve the learning efficiency of the students. In order to increase the probability of the algorithm jumping out of the local optimum, the reverse learning strategy is combined to carry out small probability mutation. The performance test based on benchmark function verifies the correctness of the above analysis. The MATLAB/Simulink simulation shows that the algorithm can effectively identify the electrical parameters of PMSM, and has good convergence and reliability. Considering the chattering phenomenon of sliding mode structure, the chattering mechanism of sliding mode control is proved from the angle of mathematics. On the basis of this, an improved sliding mode observer is designed to observe its rotational speed and position combined with PMSM mathematical model in static coordinate system. Aiming at the stability of the system caused by high frequency buffeting, the observer uses the segmented hyperbolic tangent function as the switching function and the variable sliding mode gain to weaken the chattering. Considering the effect of parameter uncertainty on observation accuracy, the stator resistance estimation is introduced in the observation process, and the observer parameters are revised in real time to further improve the observation accuracy. At the same time, the information of rotor position and velocity is estimated by fractional order phase-locked loop (FPLL), which effectively avoids the computational complexity caused by traditional phase compensation. The effectiveness of the improved synovial observer is verified by simulating the rotational speed and position under different operating conditions in MATLAB/Simulink environment.
【學(xué)位授予單位】：江南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM341;TP273

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