本文關(guān)鍵詞：基于神經(jīng)網(wǎng)絡(luò)轉(zhuǎn)速估計(jì)的異步電機(jī)矢量控制系統(tǒng)研究　出處：《湖北工業(yè)大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 異步電機(jī) 矢量控制 模糊PID 轉(zhuǎn)速估計(jì) 神經(jīng)網(wǎng)絡(luò)

【摘要】：傳統(tǒng)交流調(diào)速的難題一直阻礙著交流異步電機(jī)的發(fā)展,而矢量控制技術(shù)可以使交流電機(jī)獲得直流電機(jī)的控制特性。為了實(shí)現(xiàn)高速高精度調(diào)速要求,轉(zhuǎn)速閉環(huán)控制是核心,故高效智能的控制算法是矢量控制系統(tǒng)的性能好壞的關(guān)鍵。由于編碼器等速度傳感器在惡劣環(huán)境下存在精度低、穩(wěn)定性差等問(wèn)題,利用智能算法對(duì)電機(jī)轉(zhuǎn)速進(jìn)行實(shí)時(shí)估計(jì),從而實(shí)現(xiàn)基于矢量控制技術(shù)的無(wú)速度傳感器電機(jī)控制系統(tǒng)是國(guó)內(nèi)外交流異步電機(jī)控制研究的熱點(diǎn)所在。本文在深入研究矢量控制技術(shù)基礎(chǔ)上,首先對(duì)控制系統(tǒng)的閉環(huán)控制算法進(jìn)行改進(jìn),之后取代傳統(tǒng)編碼器,轉(zhuǎn)而利用智能算法估計(jì),針對(duì)無(wú)速度傳感器矢量控制系統(tǒng)展開(kāi)研究。取得的成果如下。(1)基于矢量控制技術(shù)實(shí)現(xiàn)解耦控制。本文被控對(duì)象為三相交流異步電機(jī),首先分析其數(shù)學(xué)模型,針對(duì)其數(shù)學(xué)模型非線性、強(qiáng)耦合等數(shù)學(xué)特性導(dǎo)致調(diào)速難的問(wèn)題,在分析了矢量控制技術(shù)原理之后,利用其實(shí)現(xiàn)對(duì)定子電流的解耦,實(shí)現(xiàn)勵(lì)磁與轉(zhuǎn)矩分量解耦控制,從而獲得直流電機(jī)的控制特性。(2)利用模糊控制算法改進(jìn)傳統(tǒng)采用PID算法的轉(zhuǎn)速控制器,實(shí)現(xiàn)高速高精度矢量控制系統(tǒng)。在控制系統(tǒng)中,結(jié)合模糊控制與PID控制的特點(diǎn),采用模糊PID控制算法實(shí)現(xiàn)矢量控制系統(tǒng)閉環(huán)控制,從而解決了傳統(tǒng)PID在復(fù)雜情況下無(wú)法實(shí)現(xiàn)高速高精度控制性能的問(wèn)題,并基于華中數(shù)控五軸數(shù)控機(jī)床的主軸控制系統(tǒng)進(jìn)行了相關(guān)實(shí)驗(yàn),應(yīng)用傳統(tǒng)PID控制器與模糊PID控制器進(jìn)行對(duì)比實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果表明模糊PID在響應(yīng)速度、控制超調(diào)及穩(wěn)態(tài)誤差方面較傳統(tǒng)PID算法有顯著的優(yōu)勢(shì)。(3)利用神經(jīng)網(wǎng)絡(luò)算法估計(jì)轉(zhuǎn)速,實(shí)現(xiàn)基于矢量控制的無(wú)速度傳感器高速高精度控制系統(tǒng)。針對(duì)矢量控制系統(tǒng)中,傳統(tǒng)傳感器成本高、使用環(huán)境有限等問(wèn)題,采用BP神經(jīng)網(wǎng)絡(luò)對(duì)轉(zhuǎn)速進(jìn)行估計(jì),設(shè)計(jì)了神經(jīng)網(wǎng)絡(luò)轉(zhuǎn)速估計(jì)模型與相應(yīng)學(xué)習(xí)算法。并針對(duì)BP神經(jīng)網(wǎng)絡(luò)算法在轉(zhuǎn)速估計(jì)方面存在的問(wèn)題,提出基于動(dòng)量法與啟發(fā)式預(yù)處理法改進(jìn)的神經(jīng)網(wǎng)絡(luò)算法。利用Maltab搭建系統(tǒng)模型仿真,對(duì)工作性能進(jìn)行驗(yàn)證。證明了BP神經(jīng)網(wǎng)絡(luò)估計(jì)的轉(zhuǎn)速可以很好的跟蹤實(shí)際轉(zhuǎn)速,改進(jìn)BP神經(jīng)網(wǎng)絡(luò)離線訓(xùn)練速度更快更穩(wěn)定,工作過(guò)程中具有更高的精度。
[Abstract]:The traditional AC speed regulation problem has been hampering the development of AC asynchronous motor, and vector control technology can make AC motor obtain the control characteristics of DC motor, in order to achieve high speed and high precision speed regulation requirements. Closed-loop speed control is the core, so efficient and intelligent control algorithm is the key to the performance of vector control system. The intelligent algorithm is used to estimate the motor speed in real time. Therefore, the speed sensorless motor control system based on vector control technology is a hot spot in the research of AC asynchronous motor control at home and abroad. Firstly, the closed-loop control algorithm of the control system is improved, then instead of the traditional encoder, the intelligent algorithm is used to estimate. The research of speed sensorless vector control system is carried out. The results are as follows: 1) decoupling control based on vector control technology. The object of this paper is three-phase AC asynchronous motor. Firstly, this paper analyzes its mathematical model, aiming at the difficulty of speed regulation caused by nonlinear and strong coupling of its mathematical model, after analyzing the principle of vector control technology, it realizes decoupling of stator current. The control characteristics of DC motor are obtained by decoupling the excitation and torque components. The fuzzy control algorithm is used to improve the traditional speed controller using PID algorithm. In the control system, combined with the characteristics of fuzzy control and PID control, the closed loop control of vector control system is realized by using fuzzy PID control algorithm. Thus solving the problem that traditional PID can not achieve high speed and high precision control performance under complex circumstances, and based on the spindle control system of Huazhong CNC five-axis CNC machine tool, the related experiments are carried out. The comparison between the traditional PID controller and the fuzzy PID controller is carried out. The experimental results show that the response speed of fuzzy PID is high. Control overshoot and steady-state error has a significant advantage over the traditional PID algorithm.) the neural network algorithm is used to estimate the rotational speed. The speed sensorless high speed and high precision control system based on vector control is realized. BP neural network is used to estimate the speed of the vector control system in view of the problems of high cost and limited use environment of the traditional sensor in the vector control system. The neural network speed estimation model and the corresponding learning algorithm are designed, and the BP neural network algorithm in speed estimation problems. An improved neural network algorithm based on momentum method and heuristic preprocessing method is proposed, and the system model simulation is built with Maltab. It is proved that the estimated speed of BP neural network can track the actual speed very well, and the speed of off-line training of improved BP neural network is faster and more stable, and the working process has higher precision.
【學(xué)位授予單位】：湖北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TM343;TP273

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