基于Hammerstein-like模型的超磁致伸缩作动器建模与控制

柳萍; 毛剑琴; 张伟; 周克敏

基于Hammerstein-like模型的超磁致伸缩作动器建模与控制

1.
北京航空航天大学自动化科学与电气工程学院, 北京 100191
2. 美国路易斯安那州立大学电气工程与计算机系, 巴屯鲁日 70803

基金项目: 国家自然科学基金资助项目(91016006,91116002); 中央高校基本科研业务费专项资金资助项目(30420111109,30420120305,SWJTU11ZT06); 路易斯安那州大学董事会资金资助项目

详细信息

中图分类号: TP 18
计量
- 文章访问数: 1470
- HTML全文浏览量: 111
- PDF下载量: 407
- 被引次数: 0
出版历程
- 收稿日期: 2012-07-23
- 网络出版日期: 2013-07-30

Modeling and control of giant magnetostrictive actuators based on Hammerstein-like model

1.
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
2. Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge 70803, USA

摘要

摘要: 超磁致伸缩作动器的率相关迟滞非线性成为其在工程应用中的一大阻碍因素.通过使用特殊建模激励信号,基于最小二乘支持向量机建立了一定频率范围内的统一率相关Hammerstein-like迟滞非线性模型,该模型能够保证其建模频率范围内单频和复合频率的模型泛化性.在此模型基础上,设计了前馈逆补偿与PID (Proportional-Integral-Derivative)反馈控制相结合的复合控制策略,针对一定频率范围内的所有单频和复合频率的输入信号,该控制器都能够保证其跟踪控制效果,最后通过实验实时跟踪控制结果进一步验证了所设计控制器的有效性.
- 超磁致伸缩作动器 /
- 率相关迟滞非线性 /
- Hammerstein-like模型 /
- 最小二乘支持向量机 /
- 建模 /
- 跟踪控制
Abstract: The rate-dependent hysteresis in giant magnetostrictive materials is a major impediment to the application of such material in actuators. A Hammerstein-like model based on the least square support vector machines (LS-SVM) was proposed to model the rate-dependent hysteresis system. It was possible to construct a unique dynamic model in a given frequency range for a rate-dependent hysteresis system using the sinusoidal scanning signals as the training set of signals for the linear dynamic subsystem of the Hammerstein-like model, which guaranteed an outstanding generalization ability of frequency. Subsequently, a proportional-integral-derivative (PID) feedback control scheme combined with a feed-forward compensation was implemented to a magnetostrictive smart structure for real-time precise trajectory tracking. Simulations and experiments on a giant magnetostrictive actuator (GMA) verify both the effectiveness and the practicality of the proposed modeling and control methods.
- giant magnetostrictive actuator /
- rate-dependent hysteresis /
- Hammerstein-like model /
- least square support vector machines (LS-SVM) /
- modeling /
- tracking control

HTML全文

参考文献(18)

[1]	Oh J,Bernstein D S.Piecewise linear identification for the rate-independent and rate-dependent Duhem hysteresis models [J].IEEE Transactions on Automatic Control,2007,52(3):576-582
[2]	Yu Y,Xiao Z,Naganathan N G,et al.Dynamic Preisach modeling of hysteresis for the piezoceramic actuator system [J].Mechanism and Machine Theory,2002,37(1):75-89
[3]	Tan U X,Win T L,Shee C Y,et al.Rate-dependent hysteresis model of piezoelectric using singularity free Prandtl-Ishlinskii model [C]// Janeiph X.Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation.Jacksonville:IEEE,2007:356-361
[4]	Janaideh M A,Rakheja S,Su C Y.Experimental characterization and modeling of rate-dependent hysteresis of a piezoceramic actuator [J].Mechatronics,2009,19(5):656-670
[5]	Oh J,Bernstein D S.Identification of rate-dependent hysteresis using the semilinear Duhem model [C]// Perter J.Proceeding of the 2004 American Control Conference.Boston:IEEE,2004:4776-4781
[6]	Lien J P,York A,Fang T,et al.Modeling piezoelectric actuators with hysteretic recurrent neural networks [J].Sensors and Actuators A:Physical,2010,163(2):516-525
[7]	Mao J Q,Ding H S.Intelligent modeling and control for rate-dependent hysteresis system [J].Science in China (Series F:Information Sciences),2009,39(3):289-304
[8]	Zhang X L,Tan Y H,Su M Y,et al.Neural networks based identification and compensation of rate-dependent hysteresis in piezoelectric actuators [J].Physica B:Condensed Matter,2010,405(12):2687-2693
[9]	Chen X K,Hisayama T,Su C Y.Pseudo-inverse-based adaptive control for uncertain discrete time systems preceded by hysteresis [J].Automatica,2009,45(2):469-476
[10]	Feng Y,Rabbath C A,Hong H,et al.Robust control for shape memory alloy micro-actuators based flap positioning system [C]//Gero P.Proceedings of the American Control Conference,Baltimore:IEEE,2010:4181-4186
[11]	Oates W S,Smith R C.Nonlinear optimal control techniques for vibration attenuation using magnetostrictive actuators [J].Journal of Intelligent Material Systems and Structures,2008,19(2):193-209
[12]	Eskinat E,Johnson S H,Luyben W L.Use of Hammerstein models in identification of nonlinear systems [J].AIChE Journal,1991,37(2):255-268
[13]	Rochdi Y,Giri F,Gning J B,et al.Identification of block-oriented systems in the presence of nonparametric input nonlinearities of switch and backlash types [J].Automatica,2010,46(5):864-877
[14]	Suykens J A K,Gestel T V,Brabantor J D,et al.Least squares support vector machines [M].New York:World Scientific,2002:196-201
[15]	Shi Y H,Eberhart R C.Empirical study of particle swarm optimization [C]//Shi Y H.Proceedings of Congress on Evolutionary Computation.Washington:IEEE,1999:1945-1950
[16]	Mao J Q,Ding H S,Ma Y H.Fuzzy dynamic model of a giant magnetostrictive actuator [J].Materials Science Forum,2007,546-549:2183-2188
[17]	Zhang H B,Jiang C B,Wang Z B,et al.Effect of compressive stress on magnetostriction hysteresis of <110> oriented Tb_0.29Dy_0.48Ho_0.23Fe₂ crystal [J].Journal of Alloys and Compounds,2009,475(1/2):35-37
[18]	Hunt K J,Sbarbaro D.Neural networks for nonlinear internal model control [J].IEE Proceedings-D of Control Theory and Applications,1991,138(5):431-438