Modeling of Non-Monotonic Hysteresis Behavior in VO2-Coated Microactuators

Author(s):  
Jun Zhang ◽  
Emmanuelle Merced ◽  
Nelson Sepúlveda ◽  
Xiaobo Tan

Vanadium dioxide (VO2) undergoes a thermally induced solid-to-solid phase transition. A VO2-coated silicon cantilever demonstrates large change in its bending curvature across its phase transition. Due to phase transition and thermal expansion effects, the curvature – temperature hysteresis in VO2 actuators comes with a non-monotonic hysteretic behavior, introducing new challenges in its modeling. Motivated by the underlying physics, in this paper we present a novel model that combines a monotonic Preisach hysteresis operator with a linear operator. A constrained least square scheme is proposed to estimate the model parameters. For comparison purposes, we also consider a Preisach operator with a signed weighting function, and a hybrid model consisting of a monotonic Preisach operator for the curvature within the transition and linear operators outside the transition. Experimental results confirm the effectiveness of the proposed model.

2018 ◽  
Vol 1 (1) ◽  
pp. 022-032
Author(s):  
Science Nature

A widely used estimation method in estimating regression model parameters is the ordinary least square (OLS) that minimizes the sum of the error squares. In addition to the ease of computing, OLS is a good unbiased estimator as long as the error component assumption ()  in the given model is met. However, in the application, it is often encountered violations of assumptions. One of the violation types is the violation of distributed error assumption which is caused by the existence of the outlier on observation data. Thus, a solid method is required to overcome the existence of outlier, that is Robust Regression. One of the Robust Regression methods commonly used is robust MM method. Robust MM method is a combination of breakdown point and high efficiency. Results obtained based on simulated data generated using SAS software 9.2, shows that the use of objective weighting function tukey bisquare is able to overcome the existence of extreme outlier. Furthermore, it is determined that the value of tuning constant c with Robust MM method is 4.685 and it is obtained95% of efficiency. Thus, the obtained breakdown point is 50%.    


2018 ◽  
Vol 1 (1) ◽  
pp. 022-032
Author(s):  
Science Nature

A widely used estimation method in estimating regression model parameters is the ordinary least square (OLS) that minimizes the sum of the error squares. In addition to the ease of computing, OLS is a good unbiased estimator as long as the error component assumption ()  in the given model is met. However, in the application, it is often encountered violations of assumptions. One of the violation types is the violation of distributed error assumption which is caused by the existence of the outlier on observation data. Thus, a solid method is required to overcome the existence of outlier, that is Robust Regression. One of the Robust Regression methods commonly used is robust MM method. Robust MM method is a combination of breakdown point and high efficiency. Results obtained based on simulated data generated using SAS software 9.2, shows that the use of objective weighting function tukey bisquare is able to overcome the existence of extreme outlier. Furthermore, it is determined that the value of tuning constant c with Robust MM method is 4.685 and it is obtained95% of efficiency. Thus, the obtained breakdown point is 50%.    


2021 ◽  
pp. 1-9
Author(s):  
Baigang Zhao ◽  
Xianku Zhang

Abstract To solve the problem of identifying ship model parameters quickly and accurately with the least test data, this paper proposes a nonlinear innovation parameter identification algorithm for ship models. This is based on a nonlinear arc tangent function that can process innovations on the basis of an original stochastic gradient algorithm. A simulation was carried out on the ship Yu Peng using 26 sets of test data to compare the parameter identification capability of a least square algorithm, the original stochastic gradient algorithm and the improved stochastic gradient algorithm. The results indicate that the improved algorithm enhances the accuracy of the parameter identification by about 12% when compared with the least squares algorithm. The effectiveness of the algorithm was further verified by a simulation of the ship Yu Kun. The results confirm the algorithm's capacity to rapidly produce highly accurate parameter identification on the basis of relatively small datasets. The approach can be extended to other parameter identification systems where only a small amount of test data is available.


2016 ◽  
Vol 42 (2) ◽  
pp. 172-176 ◽  
Author(s):  
Yu. S. Tveryanovich ◽  
S. V. Fokina ◽  
A. V. Kurochkin ◽  
E. N. Borisov ◽  
M. G. Krzhizhanovskaya ◽  
...  

2010 ◽  
Vol 63 (4) ◽  
pp. 544 ◽  
Author(s):  
Anja-Verena Mudring

Ionic liquids (ILs) have become an important class of solvents and soft materials over the past decades. Despite being salts built by discrete cations and anions, many of them are liquid at room temperature and below. They have been used in a wide variety of applications such as electrochemistry, separation science, chemical synthesis and catalysis, for breaking azeotropes, as thermal fluids, lubricants and additives, for gas storage, for cellulose processing, and photovoltaics. It has been realized that the true advantage of ILs is their modular character. Each specific cation–anion combination is characterized by a unique, characteristic set of chemical and physical properties. Although ILs have been known for roughly a century, they are still a novel class of compounds to exploit due to the vast number of possible ion combinations and one fundamental question remains still inadequately answered: why do certain salts like ILs have such a low melting point and do not crystallize readily? This Review aims to give an insight into the liquid–solid phase transition of ILs from the viewpoint of a solid-state chemist and hopes to contribute to a better understanding of this intriguing class of compounds. It will introduce the fundamental theories of liquid–solid-phase transition and crystallization from melt and solution. Aside form the formation of ideal crystals the development of solid phases with disorder and of lower order like plastic crystals and liquid crystals by ionic liquid compounds are addressed. The formation of ionic liquid glasses is discussed and finally practical techniques, strategies and methods for crystallization of ionic liquids are given.


RSC Advances ◽  
2016 ◽  
Vol 6 (2) ◽  
pp. 859-865 ◽  
Author(s):  
Changping Guo ◽  
Dunju Wang ◽  
Bing Gao ◽  
Jun Wang ◽  
Bo Luo ◽  
...  

The comparison of solid–solid phase transition (ε → γ polymorph) of CL-20 and Cl-20/composites revealed by DSC curves.


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