Fuzzy modeling of a piezoelectric actuator

International Journal of Precision Engineering and Manufacturing

Volumn 13, Issue 5, 2012, Pages 663-670

  Mohammadzaheri, Morteza ^a   Grainger, Steven ^a   Bazghaleh, Mohsen ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

ANFIS; Black box modeling; Fuzzy; Input and output extrema; Input arrangement; Piezoelectric actuator

Indexed keywords

FUZZY INFERENCE; FUZZY LOGIC; FUZZY NEURAL NETWORKS; PIEZOELECTRICITY;

ANFIS; BLACK-BOX MODEL; FUZZY; INPUT AND OUTPUTS; INPUT ARRANGEMENT;

PIEZOELECTRIC ACTUATORS;

EID: 84861875016     PISSN: 12298557     EISSN: None     Source Type: Journal    
DOI: 10.1007/s12541-012-0086-3     Document Type: Article

References (50)

1. Zhang, X. L., Tan, Y. H., Su, M. Y. and Xie, Y. Q., "Neural Networks Based Identification and Compensation of Rate-Dependent Hysteresis in Piezoelectric Actuators," Physica B: Physics of Condensed Matter, Vol. 405, No. 12, pp. 2687-2693, 2010.
2. Soderkvist, J., "Using Fea to Treat Piezoelectric Low-Frequency Resonators," IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Vol. 45, No. 3, pp. 815-823, 1998.
3. Han, J. H., Cho, K. D., Youn, S. H. and Lee, I., "Vibration and Actuation Characteristics of Composite Structures with a Bonded Piezo-Ceramic Actuator," Smart Mater. Struct., Vol. 8, No. 1, pp. 136-143, 1999.
4. Wang, G. and Wereley, N. M., "Frequency Response of Beams with Passively Constrained Damping Layers and Piezo-Actuators," Proc. of SPIE, Vol. 3327, pp. 44-60, 1998.
5. Boukari, A. F., Carmona, J. C., Moraru, G., Malburet, F., Chaaba, A. and Douimi, M., "Piezo-Actuators Modeling for Smart Applications," Mechatronics, Vol. 21, No. 1, pp. 339-349, 2011.
6. Xie, W. F., Fu, J., Yao, H. and Su, C. Y., "Neural Network-Based Adaptive Control of Piezoelectric Actuators with Unknown Hysteresis," International Journal of Adaptive Control and Signal Processing, Vol. 23, No. 1, pp. 30-54, 2009.
7. Zhang, J., Wang, E. and Gao, R., "Neural Network Predictive Control for Piezoelectric Smart Structures," ASME 9th Biennial Conference on Engineering Systems Design and Analysis, Vol. 2, Paper No. ESDA2008-59094, pp. 417-421, 2008.
8. Meeker, T. R., "Publication and Proposed Revision of ANSI/IEEE Standard 176-1987 "ANSI/IEEE Standard on Piezoelectricity", IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Vol. 43, No. 5, pp. 717-718, 1996.
9. Song, D. W. and Li, C. J., "Modeling of Piezo Actuator's Nonlinear and Frequency Dependent Dynamics," Mechatronics, Vol. 9, No. 4, pp. 391-410, 1999.
10. Jung, S. B. and Kim, S. W., "Improvement of Scanning Accuracy of Pzt Piezoelectric Actuators by Feedforward Model-Reference Control," Precision Engineering, Vol. 16, No. 1, pp. 49-55, 1994.
11. Leigh, T. D. and Zimmerman, D. C., "An Implicit Method for the Nonlinear Modelling and Simulation of Piezoceramic Actuators Displaying Hysteresis," 112th ASME Winter Annual Meeting, pp. 57-63, 1991.
12. Rakotondrabe, M., "Bouc-Wen Modeling and Inverse Multiplicative Structure to Compensate Hysteresis Nonlinearity in Piezoelectric Actuators," IEEE Transactions on Automation Science and Engineering, Vol. 8, No. 2, pp. 428-431, 2011.
13. Preisach, F., "Uber Die Magnetische Nachwirkung," Zeitschrift für Physik, Vol. 94, No. 5-6, pp. 277-302, 1935.
14. Ge, P. and Jouaneh, M., "Modeling Hysteresis in Piezoceramic Actuators," Precision Engineering, Vol. 17, No. 3, pp. 211-221, 1995.
15. Liaw, H. C. and Shirinzadeh, B., "Robust Adaptive Constrained Motion Tracking Control of Piezo-Actuated Flexure-Based Mechanisms for Micro/Nano Manipulation," IEEE Transactions on Industrial Electronics, Vol. 58, No. 4, pp. 1406-1415, 2011.
16. Zhang, Y. D., Fang, Y. C., Zhou, X. W. and Dong, X. K., "Image-Based Hysteresis Modeling and Compensation for an Afm Piezo-Scanner," Asian Journal of Control, Vol. 11, No. 2, pp. 166-174, 2009.
17. Zareinejad, M., Ghidary, S. S., Rezaei, S. M. and Abdullah, A., "Precision Control of a Piezo-Actuated Micro Telemanipulation System," Int. J. Precis. Eng. Manuf., Vol. 11, No. 1, pp. 55-65, 2010.
18. Li, C. and Tan, Y., "A Neural Networks Model for Hysteresis Nonlinearity," Sensors and Actuators A: Physical, Vol. 112, No. 1, pp. 49-54, 2004.
19. Dupre, L., Van Keer, R. and Melkebeek, J., "Generalized Scalar Preisach Model for Grain Oriented Materials Excited Along Arbitrary Directions," Journal of Applied Physics, Vol. 89, No. 11, pp. 7245-7247, 2001.
20. Ge, P. and Jouaneh, M., "Generalized Preisach Model for Hysteresis Nonlinearity of Piezoceramic Actuators," Precision Engineering, Vol. 20, No. 2, pp. 99-111, 1997.
21. Han, Y. and Zhu, J., "Implementation Procedure for the Generalized Moving Preisach Model Based on a First Order Reversal Curve Diagram," Rare Metals, Vol. 28, No. 4, pp. 355-360, 2009.
22. Yu, Y. H., Naganathan, N. and Dukkipati, R., "Preisach Modeling of Hysteresis for Piezoceramic Actuator System," Mechanism and Machine Theory, Vol. 37, No. 1, pp. 49-59, 2002.
23. Makaveev, D., Dupre, L., De Wulf, M. and Melkebeek, J., "Modeling of Quasistatic Magnetic Hysteresis with Feed-Forward Neural Networks," Journal of Applied Physics, Vol. 89, No. 11, pp. 6737-6739, 2001.
24. Sixdenier, F., Scorretti, R., Marion, R. and Morel, L., "Quasistatic Hysteresis Modeling with Feed-Forward Neural Networks: Influence of the Last but One Extreme Values," Journal of Magnetism and Magnetic Materials, Vol. 320, No. 20, pp. E992-E996, 2008.
25. Dong, R., Tan, Y. H., Chen, H. and Xie, Y. Q., "A Neural Networks Based Model for Rate-Dependent Hysteresis for Piezoceramic Actuators," Sensors and Actuators A: Physical, Vol. 143, No. 2, pp. 370-376, 2008.
26. Yang, X. F., Li, W., Wang, Y. Q. and Ye, G., "Modeling Hysteresis in Piezo Actuator Based on Neural Networks," Advances in Computation and Intelligence, Vol. 5370, pp. 290-296, 2008.
27. Dang, X. J. and Tan, Y. H., "Rbf Neural Networks Hysteresis Modelling for Piezoceramic Actuator Using Hybrid Model," Mechanical Systems and Signal Processing, Vol. 21, No. 1, pp. 430-440, 2007.
28. Lin, F. J., Shieh, H. J., Huang, P. K. and Teng, L. T., "Adaptive Control with Hysteresis Estimation and Compensation Using Rfnn for Piezo-Actuator," IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Vol. 53, No. 9, pp. 1649-1661, 2006.
29. Lin, F. J., Shieh, H. J. and Huang, P. K., "Adaptive Wavelet Neural Network Control with Hysteresis Estimation for Piezo-Positioning Mechanism," IEEE Transactions on Neural Networks, Vol. 17, No. 2, pp. 432-444, 2006.
30. Deng, L. and Tan, Y. H., "Modeling Hysteresis in Piezoelectric Actuators Using Narmax Models," Sensors and Actuators A: Physical, Vol. 149, No. 1, pp. 106-112, 2009.
31. Hwang, C. L., Jan, C. and Chen, Y. H., "Piezomechanics Using Intelligent Variable-Structure Control," IEEE Transactions on Industrial Electronics, Vol. 48, No. 1, pp. 47-59, 2001.
32. Ying, H., "General Siso Takagi-Sugeno Fuzzy Systems with Linear Rule Consequent Are Universal Approximators," IEEE Transactions on Fuzzy Systems, Vol. 6, No. 4, pp. 582-587, 1998.
33. Ying, H., "General Takagi-Sugeno Fuzzy Systems Are Universal Approximators," IEEE International Conference on Fuzzy Systems Proceedings, Vol. 1, pp. 819-823, 1998.
34. Chen, T. P. and Chen, H., "Approximation Capability to Functions of Several Variables, Nonlinear Functionals, and Operators by Radial Basis Function Neural Networks," IEEE Transactions on Neural Networks, Vol. 6, No. 4, pp. 904-910, 1995.
35. Chen, T. P. and Chen, H., "Universal Approximation to Nonlinear Operators by Neural Networks with Arbitrary Activation Functions and Its Application to Dynamical-Systems," IEEE Transactions on Neural Networks, Vol. 6, No. 4, pp. 911-917, 1995.
36. Chen, T. P., Chen, H. and Liu, R. W., "Approximation Capability in C((R)over-Bar(N)) by Multilayer Feedforward Networks and Related Problems," IEEE Transactions on Neural Networks, Vol. 6, No. 1, pp. 25-30, 1995.
37. Park, J. and Sandberg, I. W., "Approximation and Radial-Basis-Function Networks," Neural Computation, Vol. 5, No. 2, pp. 305-316, 1993.
38. Zhang, X. L., Tan, Y. H. and Su, M. Y., "Modeling of Hysteresis in Piezoelectric Actuators Using Neural Networks," Mechanical Systems and Signal Processing, Vol. 23, No. 8, pp. 2699-2711, 2009.
39. Ghaffari, A., Mehrabian, A. R. and Mohammad-Zaheri, M., "Identification and Control of Power Plant De-Superheater Using Soft Computing Techniques," Engineering Applications of Artificial Intelligence, Vol. 20, No. 2, pp. 273-287, 2007.
40. Jang, J.-S. R., Sun, C.-T. and Mizutani, E., "Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence," Prentice Hall, 2006.
41. Mathworks, "Fuzzy Logic Toolbox™ User's Guide," 2011.
42. Nelles, O., "Nonlinear System Identfication," Springer, 2001.
43. Mohammadzaheri, M. and Chen, L., "Intelliegnt Predictive Control of Model Helicopters' Yaw Angle," Asian Journal of Control, Vol. 12, No. 6, pp. 1-13, 2010.
44. Mohammadzaheri, M., Chen, L., Mirsepahi, A., Ghanbari, M. and Prime, Z., "Hybrid Intelligent Control of an Infrared Dryer," The 38th Australasian Conference of Chemical Engineering, pp. 1-10, 2010.
45. Zhang, X. L. and Tan, Y. H., "A Hybrid Model for Rate-Dependent Hysteresis in Piezoelectric Actuators," Sensors and Actuators A: Physical, Vol. 157, No. 1, pp. 54-60, 2010.
46. Kim, I., Kim, Y. S. and Park, E. C., "Sliding Mode Control of the Inchworm Displacement with Hysteresis Compensation," Int. J. Precis. Eng. Manuf., Vol. 10, No. 3, pp. 43-49, 2009.
47. Ahmadpour Khanghashlaghi, M., Yue, W. L. and Mohammadzaheri, M., "Neuro-Fuzzy Modelling of Workers Trip Production," The 32nd Australasian Transport Research Forum, 2009.
48. Mohammadzaheri, M., Chen, L., Ghaffari, A. and Willison, J., "A Combination of Linear and Nonlinear Activation Functions in Neural Networks for Modeling a De-Superheater," Simulation Modelling Practice and Theory, Vol. 17, No. 2, pp. 398-407, 2009.
49. Deng, H., Li, H. X. and Wu, Y. H., "Feedback-Linearization-Based Neural Adaptive Control for Unknown Nonaffine Nonlinear Discrete-Time Systems," IEEE Transactions on Neural Networks, Vol. 19, No. 9, pp. 1615-1625, 2008.
50. Mohammadzaheri, M., Chen, L. and Grainger, S., "A Critical Review of the Most Popular Types of Neuro Control," Asian Journal of Control, Vol. 14, No. 1, pp. 1-11, 2012.