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Mems Gyro Sliding Mode Control Method Based on Disturbance Observer

A technology of interference observer and control method, which can be used in adaptive control, general control system, control/regulation system, etc., and can solve problems such as poor practicability

Active Publication Date: 2019-08-13
NORTHWESTERN POLYTECHNICAL UNIV +2
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Problems solved by technology

[0004] In order to overcome the shortcomings of poor practicability of existing MEMS gyroscope modal control methods, the present invention provides a MEMS gyroscope sliding mode control method based on disturbance observers

Method used

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  • Mems Gyro Sliding Mode Control Method Based on Disturbance Observer
  • Mems Gyro Sliding Mode Control Method Based on Disturbance Observer
  • Mems Gyro Sliding Mode Control Method Based on Disturbance Observer

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Embodiment Construction

[0066] refer to figure 1 . The specific steps of the MEMS gyro sliding mode control method based on the disturbance observer of the present invention are as follows:

[0067] (a) The dynamic model of the MEMS gyroscope considering the quadrature error is:

[0068]

[0069] Among them, m is the mass of proof mass; Ω z Input the angular velocity for the gyro; is the electrostatic driving force; x * are the acceleration, velocity and displacement of the MEMS gyroscope proof mass along the drive axis; the y * are the acceleration, velocity and displacement of the proof mass along the detection axis; d xx , d yy is the damping coefficient; k xx , k yy is the stiffness coefficient; d xy is the damping coupling coefficient, k xy is the stiffness coupling coefficient.

[0070] In order to improve the accuracy of mechanism analysis, the MEMS gyroscope dynamic model is dimensionless. Take the dimensionless time t * = ω o t, and then divide both sides of equation ...

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Abstract

The invention discloses an MEMS (Micro-electromechanical System) gyroscope sliding mode control method based on a disturbance observer, which is used for solving the technical problem of poor practicability of the existing MEMS gyroscope sliding mode control method. According to the technical scheme, the steps are as follows: designing a disturbance observer firstly, estimating and compensating disturbance in sliding mode control, thereby reducing buffeting; meanwhile, according to the prediction error and the tracking error of a neutral network, designing the combined self-adaptive rule of aneural network weight, and correcting the weight coefficient of the neural network, thereby realizing the effective dynamic estimation of unknown dynamics. According to the method, the effective dynamic estimation of unknown dynamics can be realized by designing the combined self-adaptive rule of the neural network weight and correcting the weight coefficient of the neutral network. In combinationwith the sliding mode control theory, the feed-forward compensation of the unknown dynamics of an MEMS gyroscope can be realized, and further, the control precision of the MEMS gyroscope can be improved. The disturbance observer is designed for estimating and compensating the external disturbance and effectively reducing the buffeting of a sliding mode, and is good in practicability.

Description

technical field [0001] The invention relates to a MEMS gyroscope mode control method, in particular to a MEMS gyroscope sliding mode control method based on an disturbance observer. Background technique [0002] With the development of nonlinear control technology, Park S et al. introduced advanced intelligent learning and nonlinear control theory into the modal control process of MEMS gyroscopes, making important contributions to improving the robustness of the system and improving the performance of MEMS gyroscopes . Considering the unknown and dynamically changing uncertainties and disturbances in the MEMS gyroscope system, how to realize effective learning of unknown dynamics and feed-forward compensation of sliding mode control is the key to improving gyroscope performance. [0003] In the article "Robust adaptive sliding mode control of MEMS gyroscope using T-Sfuzzy model" (Shitao Wang and Juntao Fei, "Nonlinear Dynamics", Vol. 77, No. 1–2, 2014), Juntao Fei et al. ad...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C19/5776G01C25/00G05B13/04
Inventor 许斌张睿张安龙刘瑞鑫成宇翔邵添羿赵万良吴枫谷丛林建华刘洋慕容欣刘美霞应俊
Owner NORTHWESTERN POLYTECHNICAL UNIV
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