Abstract
An approach of hysteresis modeling in piezoelectric actuators is presented based on the multi-input single-output (MISO) fuzzy system. The proposed model adopts first-order Takagi-Sugeno (T-S) fuzzy system and transforms the multi-valued hysteresis into a one-to-one mapping with the extended input space vector. The generated fuzzy subspaces (multi-dimensional fuzzy sets) assign the maximum membership degree to the input data vectors. Fewer fuzzy subspaces are obtained by introducing the nearest neighbor and super radius concepts. The consequent parameter optimization is implemented after training the fuzzy system. Experimental results demonstrate that this methodology is algorithmically easy and can achieve high modeling accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ang, W.T., Khosla, P.K., Riviere, C.N.: Feedforward controller with inverse rate-dependent model for piezoelectric actuators in trajectory-tracking applications. IEEE/ASME Transactions on Mechatronics 12(2), 134–142 (2007)
Aphale, S.S., Devasia, S., Moheimani, S.O.R.: High-bandwidth control of a piezoelectric nanopositioning stage in the presence of plant uncertainties. Nanotechnology 19(12), 125503 (2008)
Hu, H., Georgiu, H.M.S., Benmrad, R.: Enhancement of tracking ability in piezoceramic actuators subject to dynamic excitation conditions. IEEE/ASME Transactions on Mechatronics 10(2), 230–239 (2005)
Jiles, D.C., Thoelke, J.B.: Theory of ferromagnetic hysteresis determination of model parameters from experimental hysteresis loops. IEEE Transactions on Magnetics 25(5), 3928–3930 (1989)
Bashash, S., Jalili, N.: Robust multiple frequency trajectory tracking control of piezoelectrically driven micro nanopositioning systems. IEEE Transactions on Control Systems Technology 15, 867–878 (2007)
Al Janaideh, M., Rakheja, S., Su, C.Y.: Experimental characterization and modeling of rate-dependent hysteresis of a piezoceramic actuator. Mechatronics 19(5), 656–670 (2009)
Wang, L.X., Mendel, J.M.: Fuzzy basis functions, universal approximation, and orthogonal least squares learning. IEEE Transactions on Neural Networks 3(5), 807–814 (1992)
Tafazoli, M., Demirli, K.: Fuzzy modeling of hysteresis from input-ouput data. In: IFSA World Congress and 20th NAFIPS International Conference, pp. 3009–3014 (2001)
Azzerboni, B., Carpentieri, M., Finocchio, G., La Foresta, F.: A fuzzy model of scalar hysteresis on soft magnetic materials. Physica B: Condensed Matter 343(1-4), 132–136 (2004)
Xu, K., Zhang, Z., Mao, J.: Modeling of stress dependent hysteresis nonlinearity based on fuzzy tree for GMA 2008. In: Proceedings of the IEEE International Conference on Automation and Logistics, pp. 331–335 (2008)
Sugeno, M., Yasukawa, T.: A fuzzy-logic-based approach to qualitative modeling. IEEE Transactions on Fuzzy Systems 1(1), 7–31 (1993)
Wang, L.X.: Adaptive fuzzy systems and control. Prentice-Hall, Englewood Cliffs (1994)
Nie, J.: Fuzzy control of multivariable nonlinear servomechanisms with explicit decoupling scheme. IEEE Transactions on Fuzzy Systems 5(2), 304–311 (1997)
Wang, L.X., Mendel, J.M.: Generating fuzzy rules from numerical data with applications. IEEE Transactions on System, Man and Cybernetics 22(6), 1414–1427 (1992)
George, T., Haralambos, S., George, B.: A simple algorithm for training fuzzy systems using input–output data. Advances in Engineering Software 34, 247–259 (2003)
An, J., Yang, Q., Ma, Z.: Study on method of modeling and controlling of magnetostrictive material. In: 17th International Zurich Symposium on Electromagnetic Compatibility, pp. 387–390. IEEE, Piscataway (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, P., Gu, G., Lai, L., Zhu, L. (2010). Hysteresis Modeling of Piezoelectric Actuators Using the Fuzzy System. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16584-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-16584-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16583-2
Online ISBN: 978-3-642-16584-9
eBook Packages: Computer ScienceComputer Science (R0)