本文選題：感應(yīng)電機(jī)　切入點(diǎn)：參數(shù)辨識(shí)　出處：《江南大學(xué)》2017年碩士論文

【摘要】：感應(yīng)電機(jī)具有可靠性高、性能優(yōu)良等優(yōu)點(diǎn),在現(xiàn)代工業(yè)中得到了廣泛應(yīng)用。矢量控制的出現(xiàn)使感應(yīng)電機(jī)的高性能控制成為可能,但電機(jī)參數(shù)變化會(huì)對(duì)其矢量控制產(chǎn)生重要影響。為了提高感應(yīng)電機(jī)的矢量控制性能,本文對(duì)感應(yīng)電機(jī)的參數(shù)辨識(shí)和帶參數(shù)辨識(shí)的矢量控制問(wèn)題進(jìn)行了深入研究。1.針對(duì)經(jīng)典的感應(yīng)電機(jī)參數(shù)辨識(shí)模型,智能算法在辨識(shí)其參數(shù)時(shí)存在辨識(shí)精度低的問(wèn)題,提出了一種融合兩種經(jīng)典模型的改進(jìn)模型。該改進(jìn)辨識(shí)模型先用以轉(zhuǎn)子磁鏈、定子電流為狀態(tài)變量的模型,然后在此基礎(chǔ)上用以定子磁鏈、定子電流為狀態(tài)變量的模型。通過(guò)與經(jīng)典模型的對(duì)比實(shí)驗(yàn),證明了該改進(jìn)模型的正確性。蒼狼算法具有簡(jiǎn)單實(shí)用、需調(diào)節(jié)參數(shù)少、尋優(yōu)能力強(qiáng)等優(yōu)點(diǎn)�？紤]到在感應(yīng)電機(jī)矢量控制中所需參數(shù)估計(jì)不準(zhǔn)的問(wèn)題,提出了一種基于蒼狼算法的參數(shù)辨識(shí)方法。通過(guò)與粒子群算法和遺傳算法的對(duì)比實(shí)驗(yàn),仿真表明蒼狼算法具有更準(zhǔn)確的辨識(shí)能力。2.為了提升改進(jìn)模型的電感辨識(shí)精度,提出了一種變換模型I。該變換模型I以改進(jìn)模型為基礎(chǔ),循環(huán)使用兩相靜止坐標(biāo)下的兩種經(jīng)典模型。通過(guò)與上面所提改進(jìn)模型對(duì)比實(shí)驗(yàn),證明了變換模型I能夠提升電感的辨識(shí)精度。為了進(jìn)一步提升電機(jī)參數(shù)的辨識(shí)精度,在變換模型I的基礎(chǔ)上提出了一種變換模型II。變換模型II是指:循環(huán)使用兩相靜止坐標(biāo)下的兩種經(jīng)典模型,同時(shí)將一種模型辨識(shí)的最優(yōu)值作為下種模型中的一個(gè)初值。將所提出的三種模型進(jìn)行對(duì)比實(shí)驗(yàn),仿真表明以變換模型II為辨識(shí)模型時(shí)改善了電機(jī)參數(shù)的辨識(shí)效果。3.為了改善感應(yīng)電機(jī)矢量控制性能,提出了一種變結(jié)構(gòu)PID速度控制與基于模型參考自適應(yīng)(MRAS)轉(zhuǎn)子電阻在線辨識(shí)相結(jié)合的控制方法。本文將基于MRAS辨識(shí)的轉(zhuǎn)子電阻在線反饋到電機(jī)的矢量控制系統(tǒng)中�？紤]到傳統(tǒng)PID控制器參數(shù)不能在線改變并存在積分飽和現(xiàn)象,結(jié)合傳統(tǒng)PID速度控制器、anti-windup技術(shù)和模糊理論設(shè)計(jì)了一種變結(jié)構(gòu)PID速度控制器。由MATLAB仿真實(shí)驗(yàn)可以看出,所提控制器緩解了系統(tǒng)的積分飽和現(xiàn)象,減小了速度超調(diào);同時(shí)證明了在變結(jié)構(gòu)PID速度控制下基于MRAS轉(zhuǎn)子電阻辨識(shí)的有效性。
[Abstract]:Induction motor has been widely used in modern industry because of its high reliability and excellent performance.The emergence of vector control makes the high performance control of induction motor possible, but the variation of motor parameters will have an important impact on the vector control.In order to improve the vector control performance of induction motor, the parameter identification and vector control with parameter identification of induction motor are studied in this paper.Aiming at the problem of low identification accuracy in the classical parameter identification model of induction motor, an improved model combining two classical models is proposed.The improved identification model first uses the rotor flux and stator current as the state variable, and then uses the stator flux as the state variable and the stator current as the state variable.The correctness of the improved model is proved by comparison with the classical model.The algorithm has many advantages, such as simple and practical, less adjustment parameters and better searching ability.Considering the problem of inaccurate parameter estimation in vector control of induction motor, a parameter identification method based on grey wolf algorithm is proposed.By comparing with particle swarm optimization algorithm and genetic algorithm, the simulation results show that the algorithm has more accurate identification ability.In order to improve the accuracy of inductance identification of the improved model, a transformation model is proposed.The transformation model I is based on the improved model and uses two classical models in two phase stationary coordinates.By comparing with the improved model, it is proved that the transformation model I can improve the accuracy of inductor identification.In order to further improve the identification accuracy of motor parameters, a transformation model II is proposed on the basis of transformation model I.Transformation model II refers to the cyclic use of two classical models in two-phase stationary coordinates, and the optimal value of a model identification is taken as an initial value in the next model.The simulation results show that the identification effect of the motor parameters is improved by using the transformation model II as the identification model.In order to improve the vector control performance of induction motor, a control method combining variable structure PID speed control with on-line identification of rotor resistance based on model reference adaptive control is proposed.In this paper, the rotor resistance based on MRAS identification is fed back to the vector control system of the motor.Considering that the parameters of the traditional PID controller can not be changed on line and the integral saturation phenomenon exists, a variable structure PID speed controller is designed by combining the anti-windup technique and fuzzy theory of the traditional PID speed controller.The simulation results of MATLAB show that the proposed controller can reduce the integral saturation and speed overshoot of the system and prove the effectiveness of the rotor resistance identification based on MRAS under the variable structure PID speed control.
【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)】：TM346

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