Hysteresis Modeling of Piezoelectric Actuators and Feed-Forward Compensation Algorithm Research

2015 ◽  
Vol 8 (12) ◽  
pp. 331-340
Author(s):  
Yibo Li ◽  
Zhaohui Liu ◽  
Yanmei Liu
Author(s):  
Mohamad Fazli ◽  
Seyed Mahdi Rezaei ◽  
Mohamad Zareienejad

Piezoelectric actuators are convenient for micro positioning systems. Inherent hysteresis is one of the drawbacks in use of these actuators. Precise control of this actuator under changing of environmental and operational conditions, without modeling of hysteresis, is impossible. Neural networks can be used for this modeling. The ordinary feed forward neural networks can not train time dynamic relationship between input and output. Thus a certain type of networks called time delay feed forward neural networks (TDNN), are developed and is used in this paper. In the previous researches in this field, the important effect of loaded force on the actuator is ignored. This can increase the positioning error remarkably. Especially when these actuators are used in the precise grinding or machining operations. In this paper, neural network is used for hysteresis modeling with attention to the important effect of loaded force. After modeling, inverse hysteresis model is used as compensator in a feed forward way to linearize the input-output relationship. Then using PI closed loop controller and selecting suitable coefficient for it, the maximum error was decreased to less than 2 percent of the working amplitude.


2020 ◽  
Vol 316 ◽  
pp. 112431
Author(s):  
Wen Wang ◽  
Ruijin Wang ◽  
Zhanfeng Chen ◽  
Zhiqian Sang ◽  
Keqing Lu ◽  
...  

Micromachines ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 183 ◽  
Author(s):  
Jinqiang Gan ◽  
Xianmin Zhang

Hysteresis behaviors exist in piezoelectric ceramics actuators (PCAs), which degrade the positioning accuracy badly. The classical Bouc–Wen (CB–W) model is mainly used for describing rate-independent hysteresis behaviors. However, it cannot characterize the rate-dependent hysteresis precisely. In this paper, a generalized Bouc–Wen (GB–W) model with relaxation functions is developed for both rate-independent and rate-dependent hysteresis behaviors of piezoelectric actuators. Meanwhile, the nonlinear least squares method through MATLAB/Simulink is adopted to identify the parameters of hysteresis models. To demonstrate the validity of the developed model, a number of experiments based on a 1-DOF compliant mechanism were conducted to characterize hysteresis behaviors. Comparisons of experiments and simulations show that the developed model can describe rate-dependent and rate-independent hysteresis more accurately than the classical Bouc–Wen model. The results demonstrate that the developed model is effective and useful.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Junqiang Lou ◽  
Yanding Wei ◽  
Guoping Li ◽  
Yiling Yang ◽  
Fengran Xie

Trajectory planning is an effective feed-forward control technology for vibration suppression of flexible manipulators. However, the inherent drawback makes this strategy inefficient when dealing with modeling errors and disturbances. An optimal trajectory planning approach is proposed and applied to a flexible piezoelectric manipulator system in this paper, which is a combination of feed-forward trajectory planning method and feedback control of piezoelectric actuators. Specifically, the joint controller is responsible for the trajectory tracking and gross vibration suppression of the link during motion, while the active controller of actuators is expected to deal with the link vibrations after joint motion. In the procedure of trajectory planning, the joint angle of the link is expressed as a quintic polynomial function. And the sum of the link vibration energy is chosen as the objective function. Then, genetic algorithm is used to determine the optimal trajectory. The effectiveness of the proposed method is validated by simulation and experiments. Both the settling time and peak value of the link vibrations along the optimal trajectory reduce significantly, with the active control of the piezoelectric actuators.


1994 ◽  
Vol 1 (5) ◽  
pp. 473-484 ◽  
Author(s):  
Gerald T. Montague ◽  
Albert F. Kascak ◽  
Alan Palazzolo ◽  
Daniel Manchala ◽  
Erwin Thomas

This article presents a novel means for suppressing gear mesh related vibrations. The key components in this approach are piezoelectric actuators and a high-frequency, analog feed forward controller. Test results are presented and show up to a 70% reduction in gear mesh acceleration and vibration control up to 4500 Hz. The principle of the approach is explained by an analysis of a harmonically excited, general linear vibratory system.


Proceedings ◽  
2020 ◽  
Vol 64 (1) ◽  
pp. 29
Author(s):  
Cristian Napole ◽  
Oscar Barambones ◽  
Mohamed Derbeli ◽  
Mohammed Yousri Silaa ◽  
Isidro Calvo ◽  
...  

Piezoelectric Actuators (PEAs) are devices that can support large actuation forces compared to their small size and are widely used in high-precision applications where micro- and nano-positioning are required. Nonetheless, these actuators have undeniable non-linearities, the well-known ones being creep, vibration dynamics, and hysteresis. The latter originate from a combination of mechanical strain and electric field action; as a consequence, these can affect the PEA tracking performance and even reach instability. The scope of this paper is to reduce the hysteresis effect using and comparing different control strategies like feedback with a Feed-Forward (FF) structure, which is often used to compensate the non-linearities and diminish the errors due to uncertainties. In this research, black-box models are analyzed; subsequently, a classic feedback control like Proportional-Integral (PI) control is combined with the FF methods proposed separately and embedded into a dSpace platform to perform real-time experiments. Results are analyzed in-depth in terms of the error, the control signal, and the Integral of the Absolute Error (IAE). It is found that with the proposed methods, the hysteresis effect could be diminished to acceptable ranges for high-precision tracking with a satisfactory control signal.


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