基于磁致伸縮平臺(tái)的微振動(dòng)主動(dòng)控制研究
發(fā)布時(shí)間：2018-11-03 14:27
【摘要】：在精密工程及航天工程領(lǐng)域，制造、檢測(cè)過程的內(nèi)外部擾動(dòng)嚴(yán)重影響產(chǎn)品質(zhì)量或檢測(cè)質(zhì)量，因此有必要對(duì)設(shè)備所受的微振動(dòng)干擾進(jìn)行隔離和控制。為了解決這類微振動(dòng)問題，本論文以巨精密磁致伸縮平臺(tái)為研究對(duì)象，通過引入自適應(yīng)控制算法對(duì)平臺(tái)系統(tǒng)進(jìn)行精密位形驅(qū)動(dòng)和微振動(dòng)控制，進(jìn)行了一系列仿真與實(shí)驗(yàn)測(cè)試。 論文的主要研究工作如下： （1）本文首先以單個(gè)巨磁致伸縮驅(qū)動(dòng)器（GMA）為研究對(duì)象，通過受控自回歸滑動(dòng)平均模型(CARMA)與遞推增廣最小二乘法相結(jié)合來對(duì)巨磁致伸縮驅(qū)動(dòng)器實(shí)現(xiàn)在線模型辨識(shí)，辨識(shí)模型能精確描述GMA輸出位移，辨識(shí)誤差達(dá)0.23%，與Prandtl Ishlinskii模型相比，CARMA模型辨識(shí)速度更快且精度更高；將改進(jìn)的廣義預(yù)測(cè)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(shí)時(shí)性和更高的控制精度，在0-10um給定位移下，其驅(qū)動(dòng)控制誤差達(dá)0.143um。 （2）建立巨磁致伸縮驅(qū)動(dòng)器的動(dòng)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(dòng)隔振器不同連接方式對(duì)系統(tǒng)隔振性能的影響，設(shè)計(jì)基于主被動(dòng)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(duì)GMA隔振系統(tǒng)進(jìn)行微振動(dòng)控制仿真研究和閉環(huán)實(shí)驗(yàn)測(cè)試，抑制效果達(dá)到20dB。 （3）介紹了三自由度磁致伸縮平臺(tái)的全系統(tǒng)結(jié)構(gòu)，建立系統(tǒng)動(dòng)力學(xué)模型，之后進(jìn)行仿真與開環(huán)測(cè)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(cè)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(dòng)控制和微振動(dòng)控制，，仿真與實(shí)驗(yàn)結(jié)果表明，該控制算法對(duì)于三自由度磁致伸縮平臺(tái)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(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB535
[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(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB535
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