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An intelligent control method for mems gyroscopes considering unknown dynamics and external disturbances

A technology of external interference and intelligent control, which is applied in the direction of adaptive control, general control system, control/adjustment system, etc., can solve the problems of poor practicability, achieve good practicability, reduce sliding mode chattering, and improve control accuracy

Active Publication Date: 2019-08-09
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 intelligent control method considering unknown dynamics and external disturbances

Method used

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  • An intelligent control method for mems gyroscopes considering unknown dynamics and external disturbances
  • An intelligent control method for mems gyroscopes considering unknown dynamics and external disturbances
  • An intelligent control method for mems gyroscopes considering unknown dynamics and external disturbances

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Embodiment Construction

[0080] refer to figure 1 . The specific steps of the MEMS gyroscope intelligent control method considering unknown dynamics and external disturbance in the present invention are as follows:

[0081] (a) The dynamic model of the MEMS gyroscope considering the quadrature error is:

[0082]

[0083] 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.

[0084] 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...

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Abstract

The invention discloses an intelligent MEMS gyroscope control method in accordance with unknown dynamics and external disturbance, aiming at addressing poor practicality of mode control methods of current MEMS gyroscopes. The technical solution includes the following steps: firstly designing a disturbance observer, estimating and compensating external disturbance so as to reduce sliding mode buffeting; and based on fuzzy prediction errors and tracking errors, designing a composite adaptive law of a fuzzy logic weight, correcting the weight coefficient of the fuzzy logic so as to achieve effective and dynamic estimation of the unknown dynamics. According to the invention, the method herein, in accordance with the prediction errors and tracking errors, designs the composite learning updatinglaw of the fuzzy logic weight, and corrects the weight coefficient of the fuzzy logic, and finally achieves effective and dynamic estimation of the unknown dynamics. In combination with the sliding mode control theory, the method can implement forward compensation on the MEMS gyroscope in accordance with the unknown dynamics, and further increases the control precision of the MEMS gyroscope. Themethod also designs the disturbance observer so as to estimate and compensate disturbance, thus reducing sliding mode buffeting and providing excellent practicality.

Description

technical field [0001] The invention relates to a MEMS gyroscope mode control method, in particular to an MEMS gyroscope intelligent control method considering unknown dynamics and external disturbances. 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)...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
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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