NDLI: An inversion-free model predictive control with error compensation for piezoelectric actuators

Content Provider	IEEE Xplore Digital Library
Author	Weichuan Liu Long Cheng Zeng-Guang Hou Min Tan
Copyright Year	2015
Description	Author affiliation: State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China (Weichuan Liu; Long Cheng; Zeng-Guang Hou; Min Tan)
Abstract	This paper addresses an inversion-free model predictive control with error compensation for piezoelectric actuators (PEAs), which is based on a dynamic linearized multi-layer feedforward neural network model. By the proposed method, the inverse model of the inherent hysteresis in PEAs is not required, and the control law can be obtained in an explicit form. By using the technique of constrained quadratic programming, the proposed method still works well when dealing with the plant physical constraints. Moreover, an error compensation term is introduced into the control law to attenuate the steady-state error. To verify the effectiveness of the proposed method, experiments are conducted on a commercial PEA. The experiment results show that the proposed method has a good tracking performance for PEAs.
Starting Page	5489
Ending Page	5494
File Size	2091181
Page Count	6
File Format	PDF
e-ISBN	9781479986842
DOI	10.1109/ACC.2015.7172198
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Error compensation Hysteresis Mathematical model Steady-state Piezoelectric actuators Optimal control Predictive control piezoelectric actuators hysteresis neural network modeling dynamic linearization model predictive control
Content Type	Text
Resource Type	Article

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