Abstract
This chapter presents the rate-dependent hysteresis compensation of a piezoelectric nanopositioning stage using the feedforward control based on an inverse hysteresis model. Three different controllers are realized and compared, which employ Bouc–Wen model, modified Prandtl–Ishlinskii (MPI) model, and least squares support vector machines (LSSVM)-based intelligent model, respectively. Experimental studies demonstrate the superiority of LSSVM model in hysteresis modeling and compensation tasks.
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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 Trans. Mechatron. 12(2), 134–142 (2007)
Birge, B.: PSOt—a particle swarm optimization toolbox for use with Matlab. In: Proceedings of IEEE Swarm Intelligence Symposium, pp. 182–186. Indianapolis, Indiana, USA (2003)
Boukari, A.F., Carmona, J.C., Moraru, G., Malburet, F., Chaaba, A., Douimi, M.: Piezo-actuators modeling for smart applications. Mechatronics 21(1), 339–349 (2011)
De Brabanter, K., Karsmakers, P., Ojeda, F., Alzate, C., De Brabanter, J., Pelckmans, K., De Moor, B., Vandewalle, J., Suykens, J.A.K.: LS-SVMlab toolbox user’s guide version 1.7. Internal Report 10-146, ESAT-SISTA, K.U.Leuven, Leuven, Belgium (2010)
Dong, R., Tan, Y., Chen, H., Xie, Y.: A neural networks based model for rate-dependent hysteresis for piezoelectric actuators. Sens. Actuator A-Phys. 143(2), 370–376 (2008)
Ge, P., Jouaneh, M.: Tracking control of a piezoceramic actuator. IEEE Trans. Contr. Syst. Technol. 4(3), 209–216 (1996)
Janaideh, M.A., Rakheja, S., Su, C.Y.: Experimental characterization and modeling of rate-dependent hysteresis of a piezoceramic actuator. Mechatronics 19(5), 656–670 (2009)
Juhasz, L., Maas, J., Borovac, B.: Parameter identification and hysteresis compensation of embedded piezoelectric stack actuators. Mechatronics 21(1), 329–338 (2011)
Kim, J., Kang, B.: Micro-macro linear piezoelectric motor based on self-moving cell. Mechatronics 19(7), 1134–1142 (2009)
Kuhnen, K.: Modeling, identification and compensation of complex hysteretic nonlinearities: a modified Prandtl-Ishlinskii approach. Eur. J. Control 9(4), 407–421 (2003)
Li, Y., Xu, Q.: Adaptive sliding mode control with perturbation estimation and PID sliding surface for motion tracking of a piezo-driven micromanipulator. IEEE Trans. Contr. Syst. Technol. 18(4), 798–810 (2010)
Lin, C.J., Chen, S.Y.: Evolutionary algorithm based feedforward control for contouring of a biaxial piezo-actuated stage. Mechatronics 19(6), 829–839 (2009)
Suykens, J.A.K., Vandewalle, J.: Least squares support vector machine classifiers. Neural Process. Lett. 9(3), 293–300 (1999)
Suykens, J.A.K., Gestel, T.V., Brabanter, J.D., Moor, B.D., Vandewalle, J.: Least Squares Support Vector Machines. World Scientific Publishing Co., Singapore (2002)
Van Gestel, T., Suykens, J.A.K., Baestaens, D.E., Lambrechts, A., Lanckriet, G., Vandaele, B., De Moor, B., Vandewalle, J.: Financial time series prediction using least squares support vector machines within the evidence framework. IEEE Trans. Neural Netw. 12(4), 809–821 (2001)
Vong, C.M., Wong, P.K., Li, Y.P.: Prediction of automotive engine power and torque using least squares support vector machines and Bayesian inference. Eng. Appl. Artif. Intell. 19(3), 277–287 (2006)
Wong, P.K., Vong, C.M., Tam, L.M., Li, K.: Data preprocessing and modelling of electronically-controlled automotive engine power performance using kernel principal components analysis and least-square support vector machines. Int. J. Veh. Syst. Model. Test. 3(4), 312–330 (2008)
Xu, Q., Li, Y.: Dahl model-based hysteresis compensation and precise positioning control of an XY parallel micromanipulator with piezoelectric actuation. J. Dyn. Syst. Meas. Control-Trans. ASME 132(4), 041,011 (2010)
Yang, J., Bouzerdoum, A., Phung, S.L.: A training algorithm for sparse LS-SVM using compressive sampling. In: Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing, pp. 2054–2057 (2010)
Yu, S., Alici, G., Shirinzadeh, B., Smith, J.: Sliding mode control of a piezoelectric actuator with neural network compensating rate-dependent hysteresis. In: Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 3641–3645 (2005)
Yu, Y., Xiao, Z., Naganathan, N.G., Dukkipati, R.V.: Dynamic Preisach modelling of hysteresis for the piezoceramic actuator system. Mech. Mach. Theory 37(1), 75–89 (2002)
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Xu, Q., Tan, K.K. (2016). Feedforward Control Based on Inverse Hysteresis Models. In: Advanced Control of Piezoelectric Micro-/Nano-Positioning Systems. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-21623-2_2
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DOI: https://doi.org/10.1007/978-3-319-21623-2_2
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