本文選題：無(wú)刷直流電機(jī)　切入點(diǎn)：調(diào)速　出處：《太原理工大學(xué)》2017年碩士論文

【摘要】：無(wú)刷直流電機(jī)(BLDCM)由于具備構(gòu)造簡(jiǎn)單、效率高、控制方便、運(yùn)行安全可靠等特點(diǎn),出現(xiàn)后便在軍事、汽車驅(qū)動(dòng)、工業(yè)自動(dòng)化、民航等領(lǐng)域取得了普遍的應(yīng)用。與此同時(shí),由于電子、計(jì)算機(jī)、自動(dòng)控制技術(shù)的飛速發(fā)展,人們也提高了對(duì)其調(diào)控品質(zhì)的要求。所以,研究有著反應(yīng)更快、精度更高、穩(wěn)定性更好的BLDCM控制系統(tǒng)具備非常廣闊的運(yùn)用前景。本文針對(duì)傳統(tǒng)的BLDCM調(diào)速系統(tǒng)很難滿足其在高速、高精度及擾動(dòng)較大等場(chǎng)合的應(yīng)用。以智能控制算法為首要的探討對(duì)象,研究可應(yīng)用于工業(yè)焦?fàn)t自動(dòng)測(cè)溫機(jī)器人的BLDCM調(diào)速控制系統(tǒng)。根據(jù)其對(duì)運(yùn)動(dòng)有著對(duì)位要準(zhǔn)、要快、抗干擾能力要強(qiáng)及避免發(fā)生滑動(dòng)等的要求,采用基于改進(jìn)粒子群算法的模糊PID調(diào)速系統(tǒng)對(duì)測(cè)溫機(jī)器人的BLDCM運(yùn)動(dòng)部分進(jìn)行調(diào)控。首先介紹了BLDCM的組成及其運(yùn)行原理,并在理想的條件下分析了其數(shù)學(xué)模型,建立了三相電機(jī)仿真模型;緊接著經(jīng)過(guò)拉普拉斯變換后確定了其傳遞函數(shù)且在Simulink平臺(tái)下搭建了動(dòng)態(tài)仿真結(jié)構(gòu)。然后,分析了模糊控制的基本原理、組成和結(jié)構(gòu),設(shè)計(jì)了該算法的邏輯規(guī)則庫(kù),并將其與PID算法相結(jié)合,構(gòu)成的模糊PID控制算法既保留了PID算法的魯棒性,又體現(xiàn)出模糊控制的動(dòng)態(tài)調(diào)節(jié)品質(zhì),使得整個(gè)被控系統(tǒng)具備一定的自適應(yīng)能力,展現(xiàn)出模糊PID控制器的優(yōu)良特性。最后,詳細(xì)分析了標(biāo)準(zhǔn)粒子群算法的原理、執(zhí)行流程及其數(shù)學(xué)表達(dá)式,并針對(duì)該算法尋優(yōu)速度不足和容易陷入局部最優(yōu)的缺點(diǎn),采用了正交試驗(yàn)機(jī)制和模仿染色體變異機(jī)制的突變策略對(duì)傳統(tǒng)粒子群優(yōu)化算法做了改進(jìn)。通過(guò)舉例說(shuō)明了正交試驗(yàn)對(duì)算法尋優(yōu)速度和效率的提升作用。接著為了使整個(gè)算法在迭代的過(guò)程中保持良好的多樣性,仿照基因突變機(jī)理引入突變策略對(duì)算法的極值傳遞過(guò)程進(jìn)行改進(jìn),可避免過(guò)早發(fā)生聚集現(xiàn)象從而克服其陷入局部最優(yōu),并就該兩種策略的引入給出了改進(jìn)算法運(yùn)行的偽代碼。經(jīng)過(guò)MATLAB編程實(shí)現(xiàn)與用benchmark函數(shù)測(cè)試的對(duì)比實(shí)驗(yàn),證明了所用改進(jìn)策略的有效性。并將其應(yīng)用在模糊PID調(diào)節(jié)器的參數(shù)優(yōu)化問(wèn)題中,顯著提高了控制器的各項(xiàng)調(diào)控品質(zhì),使得整個(gè)BLDCM調(diào)速系統(tǒng)具備良好的精確度、響應(yīng)速度、穩(wěn)定性以及自適應(yīng)能力。
[Abstract]:BLDCM (Brushless DC Motor) has been widely used in military, automobile driving, industrial automation, civil aviation and so on, because of its simple structure, high efficiency, convenient control, safe and reliable operation and so on. Because of the rapid development of electronic, computer and automatic control technology, people also improve the quality of their control. Therefore, the research has a faster response and higher accuracy. The BLDCM control system with better stability has a very broad application prospect. In this paper, the traditional BLDCM speed control system is difficult to meet the needs of high speed, high precision and large disturbance. This paper studies the BLDCM speed control system of industrial coke oven automatic temperature measuring robot. According to the requirements of its motion alignment, fast, strong anti-interference ability and avoiding sliding, etc. A fuzzy PID speed regulating system based on improved particle swarm optimization (PSO) is used to control the BLDCM motion of the temperature measuring robot. Firstly, the composition and operation principle of BLDCM are introduced, and its mathematical model is analyzed under ideal conditions. The simulation model of three-phase motor is established, and then the transfer function is determined after Laplace transform and the dynamic simulation structure is built on Simulink platform. Then, the basic principle, composition and structure of fuzzy control are analyzed. The logic rule base of the algorithm is designed and combined with the PID algorithm. The fuzzy PID control algorithm not only retains the robustness of the PID algorithm, but also embodies the dynamic regulation quality of the fuzzy control. It makes the whole controlled system have certain adaptive ability, and shows the excellent characteristics of fuzzy PID controller. Finally, the principle, execution flow and mathematical expression of standard particle swarm optimization algorithm are analyzed in detail. Aiming at the shortcomings of the algorithm, such as insufficient optimization speed and easy to fall into local optimum, The traditional particle swarm optimization (PSO) algorithm is improved by using orthogonal experiment mechanism and mutation strategy which imitates chromosome mutation mechanism. The paper illustrates the effect of orthogonal experiment on the speed and efficiency of optimization. So that the whole algorithm has a good variety of iterations, Based on gene mutation mechanism, mutation strategy is introduced to improve the extremum transfer process of the algorithm, which can avoid premature aggregation and overcome its local optimum. The pseudo code of the improved algorithm is given for the introduction of the two strategies, and the contrast experiment between the MATLAB programming and the test with benchmark function is given. It is proved that the improved strategy is effective, and it is applied to the parameter optimization of fuzzy PID regulator, which improves the control quality of the controller, and makes the whole BLDCM speed control system have good accuracy and response speed. Stability and adaptive ability.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM33;TP273

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