From model-driven to data-driven : a review of hysteresis modeling in structural and mechanical systems

Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems. The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous methods have been developed to describe hysteresis. In this paper, a review of the available hysteretic modeling methods is carried out. Such methods are divided into: a) model-driven and b) datadriven methods. The model-driven method uses parameter identification to determine parameters. Three types of parametric models are introduced including polynomial models, differential based models, and operator based models. Four algorithms as least mean square error algorithm, Kalman filter algorithm, metaheuristic algorithms, and Bayesian estimation are presented to realize parameter identification. The data-driven method utilizes universal mathematical models to describe hysteretic behavior. Regression model, artificial neural network, least square support vector machine, and deep learning are introduced in turn as the classical data-driven methods. Model-data driven hybrid methods are also discussed to make up for the shortcomings of the two methods. Based on a multi-dimensional evaluation, the existing problems and open challenges of different hysteresis modeling methods are discussed. Some possible research directions about hysteresis description are given in the final section

Robust control of systems with output hysteresis and input saturation using a finite time stability approach

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a robust control approach for a class of nonlinear dynamic systems consisting of a linear plant connected in series with a hysteresis operator, and affected by control input saturation. Such a class of systems commonly appears in applications concerning smart materials, in particular thermal shape memory alloys wire actuators. The goal of this paper is to design a robust controller, in the form of an output PI law, which ensures set-point regulation with a desired decay rate and, at the same time, accounts for the effects of both hysteresis and input saturation. The resulting controller appears as attractive on the implementation stand-point, since no accurate hysteresis compensator is required. In order to deal with the proposed problem, the hysteretic plant is first reformulated as a linear parameter-varying system. Subsequently, a finite time stability approach is used to impose constraints on the control input. A new set of bilinear matrix inequalities is developed, in order to perform the design with reduced conservatism by properly exploiting some structural properties of the model. The effectiveness of the method is finally validated by means of a numerical case of study. © 2018 IEEE.Peer ReviewedPostprint (author's final draft

On hysteresis modeling of a piezoelectric precise positioning system under variable temperature

We propose the modeling of hysteresis nonlinearities in a piezoelectric material-based tube actuator classically employed in precise positioning applications under different sur-rounding temperatures. Beyond the voltage-to-displacement hysteresis nonlinearities they exhibit, these actuators are sensitive to the surrounding temperature. Therefore, contrary to the existing works in the literature where the two phenomena were treated individually,this paper suggests to model the hysteresis nonlinearities and the temperature effects si-multaneously. First an experimental study was performed to investigate the effects of the surrounding temperature on the voltage-to-displacement hysteresis loops of the piezoelectric tube actuators. The experimental results show that increasing the input surrounding temperature contributes an increase in the voltage-to-displacement sensitivity of the piezoelectric tube actuator under the input voltage range considered in the experimental tests. Then, two different nonlinear temperature-dependent hysteresis models a temperature-dependent (TD) electromechanical model and a temperature-dependent Prandtl-Ishlinskii model (TD-PI) were proposed to account the temperature effects on the hysteresis nonlinearity. In first, the mathematical formulation of TD-electromechanical model was presented to describe the electrical and mechanical properties of piezoelectric tube actuator. This model integrates the temperature dependent electromechanical coupling factor to model the temperature effects, the Simscape library in MATLAB-Simulink software was used to develop a physical simulation for the TD-electromechanical model. In a second time, a TD-PI model was proposed to describe the voltage-to-displacement characteristic of piezoelectric tube actuator using a proposed temperature shape function. The parameters of the two proposed models were estimated using proposed optimization algorithms based on Grey Wolf Optimizer (GWO). The modeling results demonstrate that the two proposed models can account for the hysteresis nonlinearities of the piezoelectric tube actuators under different levels of the surrounding temperatures. Finally, the analytical inverse of TD-PI model was derived and applied in feed forward manner to compensate the hysteresis nonlinearities under different levels of the surrounding temperatures