Design of Reconfigurable Planar Micro-Positioning Stages Based on Function Modules

Ding, Bingxiao; Yang, Zhixin; Xiao, Xiao; Zhang, Geng

doi:10.1109/access.2019.2894619

Cited by 21 publications

(10 citation statements)

References 41 publications

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“…Hinge. According to the field of flexure-based mechanisms [6][7][8][9][10][11][12][13][14][15], the main geometrical parameters of the flexure hinge significantly affect the output quality of the responses. In this paper, three geometrical parameters of the elliptical flexure hinge include the thickness of (h), x-axis radius (r x ), and yaxis radius (r y ), which were chosen as the design variables.…”

Section: Determination Of the Design Optimization For The Flexurementioning

confidence: 99%

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Optimization for a Flexure Hinge Using an Effective Hybrid Approach of Fuzzy Logic and Moth-Flame Optimization Algorithm

Dang

Chau

et al. 2021

Mathematical Problems in Engineering

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Flexure hinge is a critical element in a positioner of a nanoindentation tester. To effectively work, a suitable flexure hinge should simultaneously meet multiple objectives, including rotation axis shift, safety factor, and angular deflection. The main aim of this article was to illustrate a hybrid method of the Taguchi method, fuzzy logic, response surface method, and Moth-flame optimization algorithm to solve the design optimization of a flexure hinge in order to enhance the three quality characteristics of the flexure hinge. Firstly, four common flexure hinges are compared together to seek the best suitable one. Secondly, numerical experiments are gathered via the Taguchi-based detasFlex software. Thirdly, three objective functions are transferred into signal to noises in order to eliminate the unit differences. Later on, fuzzy modeling is proposed to interpolate these three objective functions into one integrated objective function. An integrated regression equation is built using the response surface method. Finally, the flexure hinge is optimized by the Moth-flame optimization algorithm. The results found that the rotation axis shift is 10.944∗10−5 mm, the high safety factor is 2.993, and the angular deflection is 52.0058∗10−3 rad. The verifications are in a suitable agreement with the forecasted results. An analysis of variance and sensitivity analysis are also performed to identify the effects and meaningful contributions of input variables on the integrated objective function. In addition, employing the Wilcoxon signed rank test and the Friedman test, the results find that the proficiency of the proposed method has more benefits than the ASO algorithm and the GA. The results of this research provide a beneficial approach for conducting complicated multiobjective optimal problems.

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Section: Determination Of the Design Optimization For The Flexurementioning

confidence: 99%

“…Currently, compliant mechanisms with flexure hinges are widely employed for accurate engineering systems [6][7][8][9][10][11]. Wadikhaye et al proposed a compact serial-kinematic scanner applied to high-speed atomic force microscopy [12].…”

Section: Introductionmentioning

confidence: 99%

Optimization for a Flexure Hinge Using an Effective Hybrid Approach of Fuzzy Logic and Moth-Flame Optimization Algorithm

Dang

Chau

et al. 2021

Mathematical Problems in Engineering

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“…[ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. One of the greatest challenge in this research field is the uncertainties produced by various factors such as the dynamic model, environmental temperature, sensors performance, and the actuators’ nonlinear characteristics [ 8 , 9 ], which make the control of micropositioning system a demanding problem.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Disturbance Observer and Deep Reinforcement Learning Based Motion Control for Micropositioners

Liang

Xiao

et al. 2022

Micromachines

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The motion control of high-precision electromechanitcal systems, such as micropositioners, is challenging in terms of the inherent high nonlinearity, the sensitivity to external interference, and the complexity of accurate identification of the model parameters. To cope with these problems, this work investigates a disturbance observer-based deep reinforcement learning control strategy to realize high robustness and precise tracking performance. Reinforcement learning has shown great potential as optimal control scheme, however, its application in micropositioning systems is still rare. Therefore, embedded with the integral differential compensator (ID), deep deterministic policy gradient (DDPG) is utilized in this work with the ability to not only decrease the state error but also improve the transient response speed. In addition, an adaptive sliding mode disturbance observer (ASMDO) is proposed to further eliminate the collective effect caused by the lumped disturbances. The micropositioner controlled by the proposed algorithm can track the target path precisely with less than 1 μm error in simulations and actual experiments, which shows the sterling performance and the accuracy improvement of the controller.

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“…The performances of these stations and of the microfactory are strongly dependent on the characteristics of these micro-positioning devices such as the production rate, flexibility, precision, and energy consumption. Different architectures of micro-positioning devices can be found in the literature and can be classified according to their architecture, either long-range actuators [1][2][3][4][5] or on an array of shortrange actuators [6][7][8][9][10]. Positioning with the help of long-range actuators is mostly carried out using the analogical principle due to their high precision and good position repeatability.…”

Section: Introductionmentioning

confidence: 99%

Planar Micro-Positioning Device Based on a 3D Digital Electromagnetic Actuator

et al. 2021

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In this paper, a novel micro-positioning device based on a 3D digital actuator is presented. The proposed system allows realizing planar motions of micro-objects, which could be implemented in several applications where micro-positioning tasks are needed such as micro-component manufacturing/assembly, biomedicine, scanning microscopy, etc. The device has three degrees of freedom, and it is able to achieve planar motions of a mobile plate in the xy-plane at two different levels along the z-axis. It consists of a hexagonal mobile part composed of a permanent magnet that can reach twelve discrete positions distributed between two z-axis levels (six at each level). Two different approaches are presented to perform positioning tasks of the plate using the digital actuator: the stick-slip and the lift-mode approaches. A comparison between these two approaches is provided on the basis of the plate displacement with respect to different current values and conveyed mass. It was observed that for a current of 2 A, the actuator is able to displace a mass of 1.15 g over a distance of 0.08 mm. The optimal positioning range of the planar device was found to be ±5.40 mm and ±7.05 mm along the x- and y-axis, respectively.

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Design of Reconfigurable Planar Micro-Positioning Stages Based on Function Modules

Cited by 21 publications

References 41 publications

Optimization for a Flexure Hinge Using an Effective Hybrid Approach of Fuzzy Logic and Moth-Flame Optimization Algorithm

Optimization for a Flexure Hinge Using an Effective Hybrid Approach of Fuzzy Logic and Moth-Flame Optimization Algorithm

Adaptive Sliding Mode Disturbance Observer and Deep Reinforcement Learning Based Motion Control for Micropositioners

Planar Micro-Positioning Device Based on a 3D Digital Electromagnetic Actuator

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