Modeling and control of hysteresis in magnetostrictive actuators

Authors:
Xiaobo Tan;John S. Baras
Affiliations:
Institute for Systems Research, University of Maryland, College Park, MD 20742, USA;Institute for Systems Research, University of Maryland, College Park, MD 20742, USA and Department of Electrical and Computer Engineering, University of Maryland, College Park, MD 20742, USA
Venue:
Automatica (Journal of IFAC)
Year:
2004

Citing 1
Cited 17

Identification of hysteresis loops

Journal of Computational Physics

Robust control for the systems preceded by hysteresis

MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
Hybrid genetic algorithms for parameter identification of a hysteresis model of magnetostrictive actuators

Neurocomputing
Brief paper: Pseudo-inverse-based adaptive control for uncertain discrete time systems preceded by hysteresis

Automatica (Journal of IFAC)
Adaptive neural control for a class of uncertain nonlinear systems in pure-feedback form with hysteresis input

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive neural control for a class of nonlinear systems with uncertain hysteresis inputs and time-varying state delays

IEEE Transactions on Neural Networks
Hysteresis compensation for smart actuators using inverse generalized Prandtl-Ishlinskii model

ACC'09 Proceedings of the 2009 conference on American Control Conference
Observer based control of piezoelectric actuators with classical Duhem modeled hysteresis

ACC'09 Proceedings of the 2009 conference on American Control Conference
Two-time-scale averaging of systems involving operators and its application to adaptive control of hysteretic systems

ACC'09 Proceedings of the 2009 conference on American Control Conference
Adaptive dynamic surface control for a class of strict-feedback nonlinear systems with unknown backlash-like hysteresis

ACC'09 Proceedings of the 2009 conference on American Control Conference
Neural network modeling and generalized predictive control for Giant Magnetostrictive actuators

CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
On the robust control of systems preceded by differential equation-based hysteresis nonlinearities

ICIRA'10 Proceedings of the Third international conference on Intelligent robotics and applications - Volume Part I
Brief paper: Why are some hysteresis loops shaped like a butterfly?

Automatica (Journal of IFAC)
Precision control of magnetostrictive actuator using dynamic recurrent neural network with hysteron

ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
A memory-based hysteresis model in piezoelectric actuators

Journal of Control Science and Engineering - Special issue on Advanced Control in Micro-/Nanosystems
Accounting for hysteresis in repetitive control design: Nanopositioning example

Automatica (Journal of IFAC)
Advanced high precision control for XY-Table

ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
Non-parametric convex identification of extended generalized Prandtl-Ishlinskii models

Automatica (Journal of IFAC)

Quantified Score

Hi-index	22.15

Visualization

Abstract

A novel dynamic model is proposed for the hysteresis in magnetostrictive actuators by coupling a Preisach operator to an ordinary differential equation, and a parameter identification method is described. An efficient inversion algorithm for a class of Preisach operators with piecewise uniform density functions is then introduced, based upon which an inverse control scheme for the dynamic hysteresis model is presented. Finally the inversion error is quantified and l"1 control theory is applied to improve the robustness of inverse compensation. Simulation and experimental results based on a Terfenol-D actuator are provided.