Mr. Rui Wang Profile

Rui Wang

at Xi’an Institute of Optics and Precision Mechanics,

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Proceedings Article | 24 June 2021 Paper

Design of secondary lens focusing mechanism for multispectral camera

Rui Wang, Xiuqin Su, Yongming Qiao, Tao Lv, Xuan Wang, Kaidi Wang, Yuan Tian

Proceedings Volume 11885, 1188512 (2021) https://doi.org/10.1117/12.2602300

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Due to the influence of mechanical environment, large range temperature change and atmospheric pressure, the space multispectral camera has a certain amount of defocus in the optical imaging system. In order to improve the imaging quality of the multispectral camera, if the traditional CAM focusing mechanism is adopted, it is difficult to meet the requirements of high precision focusing for fast response due to its disadvantages such as large volume, poor efficiency and low precision. Therefore, a new focusing mechanism is designed in this paper, which is composed of rhomboid amplifier large piezoelectric ceramic actuator, flexible hinge support structure and high-precision capacitance sensor. The mechanism drives the flexible support guide structure of the parallelogram by means of a rhomboid amplifier large PZT actuator with three points distributed uniformly and symmetrically at 120°, so that the lens base can move in a straight line along the Z direction. The high precision capacitance sensor is used as the feedback element to ensure the focusing accuracy of the mechanism reaches nanometer level. The test results show that the focusing range of this mechanism is ±21.91um, the focusing speed is 438um/s, the focusing precision is 50nm and the tilt error is 1".

Proceedings Article | 28 February 2017 Paper

Movement decoupling control for two-axis fast steering mirror

Rui Wang, Yongming Qiao, Tao Lv

Proceedings Volume 10256, 1025625 (2017) https://doi.org/10.1117/12.2257346

KEYWORDS: Neural networks, Mirrors, Adaptive control, Motion controllers, Actuators, Feedback control, Complex systems, Error analysis, Evolutionary algorithms

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Based on flexure hinge and piezoelectric actuator of two-axis fast steering mirror is a complex system with time varying, uncertain and strong coupling. It is extremely difficult to achieve high precision decoupling control with the traditional PID control method. The feedback error learning method was established an inverse hysteresis model which was based inner product dynamic neural network nonlinear and no-smooth for piezo-ceramic. In order to improve the actuator high precision, a method was proposed, which was based piezo-ceramic inverse model of two dynamic neural network adaptive control. The experiment result indicated that, compared with two neural network adaptive movement decoupling control algorithm, static relative error is reduced from 4.44% to 0.30% and coupling degree is reduced from 12.71% to 0.60%, while dynamic relative error is reduced from 13.92% to 2.85% and coupling degree is reduced from 2.63% to 1.17%.

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