【摘要】：在精密工程及航天工程領(lǐng)域，制造、檢測過程的內(nèi)外部擾動嚴(yán)重影響產(chǎn)品質(zhì)量或檢測質(zhì)量，因此有必要對設(shè)備所受的微振動干擾進(jìn)行隔離和控制。為了解決這類微振動問題，本論文以巨精密磁致伸縮平臺為研究對象，通過引入自適應(yīng)控制算法對平臺系統(tǒng)進(jìn)行精密位形驅(qū)動和微振動控制，進(jìn)行了一系列仿真與實驗測試。 論文的主要研究工作如下： （1）本文首先以單個巨磁致伸縮驅(qū)動器（GMA）為研究對象，通過受控自回歸滑動平均模型(CARMA)與遞推增廣最小二乘法相結(jié)合來對巨磁致伸縮驅(qū)動器實現(xiàn)在線模型辨識，辨識模型能精確描述GMA輸出位移，辨識誤差達(dá)0.23%，與Prandtl Ishlinskii模型相比，CARMA模型辨識速度更快且精度更高；將改進(jìn)的廣義預(yù)測控制算法（MGPC）應(yīng)用于GMA的閉環(huán)位移控制，與其它算法相比，MGPC具有更好的實時性和更高的控制精度，在0-10um給定位移下，其驅(qū)動控制誤差達(dá)0.143um。 （2）建立巨磁致伸縮驅(qū)動器的動力學(xué)模型，闡述其具有可調(diào)剛度特性。通過分析比較GMA與被動隔振器不同連接方式對系統(tǒng)隔振性能的影響，設(shè)計基于主被動隔振器串聯(lián)結(jié)構(gòu)的隔振系統(tǒng)。最后應(yīng)用上述CARMA模型和MGPC算法對GMA隔振系統(tǒng)進(jìn)行微振動控制仿真研究和閉環(huán)實驗測試，抑制效果達(dá)到20dB。 （3）介紹了三自由度磁致伸縮平臺的全系統(tǒng)結(jié)構(gòu)，建立系統(tǒng)動力學(xué)模型，之后進(jìn)行仿真與開環(huán)測試研究，分析比較模型的準(zhǔn)確性。將本文研究的基于CARMA模型的改進(jìn)廣義預(yù)測自適應(yīng)控制算法應(yīng)用于三自由度全系統(tǒng)的位形驅(qū)動控制和微振動控制，，仿真與實驗結(jié)果表明，該控制算法對于三自由度磁致伸縮平臺也同樣可以達(dá)到良好的控制精度和隔振效果。
[Abstract]:In the field of precision engineering and aerospace engineering, the internal and external disturbances of manufacturing and testing process seriously affect the quality of products or the quality of detection, so it is necessary to isolate and control the micro-vibration interference of equipment. In order to solve this kind of micro-vibration problem, a series of simulation and experimental tests are carried out by introducing adaptive control algorithm to the precise configuration drive and micro-vibration control of the platform system. The main work of this thesis is as follows: (1) in this thesis, a single giant magnetostrictive actuator (GMA) is firstly studied. The on-line model identification of giant magnetostrictive actuator is realized by combining the controlled autoregressive moving average model (CARMA) with the recursive augmented least square method. The identification model can accurately describe the output displacement of GMA, and the identification error is 0.23. Compared with Prandtl Ishlinskii model, CARMA model is faster and more accurate. The improved generalized predictive control algorithm (MGPC) is applied to the closed-loop displacement control of GMA. Compared with other algorithms, MGPC has better real-time performance and higher control precision. Under the given displacement of 0-10um, the driving control error is 0.143 um. (2) the dynamic model of giant magnetostrictive actuator is established and its adjustable stiffness is described. By analyzing and comparing the influence of different connection modes between GMA and passive isolator on the isolation performance of the system, a vibration isolation system based on the series structure of active and passive vibration isolators is designed. Finally, the microvibration control simulation and closed-loop test of GMA isolation system are carried out by using the CARMA model and MGPC algorithm, and the suppression effect is up to 20 dB. (3) the whole system structure of 3-DOF magnetostrictive platform is introduced, the dynamic model of the system is established, and then the simulation and open-loop test are carried out, and the accuracy of the model is analyzed and compared. The improved generalized predictive adaptive control algorithm based on CARMA model is applied to the configuration drive control and micro-vibration control of the three-degree-of-freedom system. The simulation and experimental results show that, The control algorithm can also achieve good control accuracy and vibration isolation for the three-DOF magnetostrictive platform.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TB535

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本文編號：2308058