Disturbance observer-based MEMS gyroscope combined learning control method

A technology of interference observer and learning control, applied in gyroscope/steering sensing equipment, adaptive control, general control system and other directions, can solve problems such as poor practicability

Active Publication Date: 2018-01-19
NORTHWESTERN POLYTECHNICAL UNIV +2
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Problems solved by technology

[0004] In order to overcome the shortcomings of the poor practicability of the modal control method of the existing MEMS gyroscope, the present invention provides a MEMS gyroscope compound learning control method based on a disturbance observer

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  • Disturbance observer-based MEMS gyroscope combined learning control method
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  • Disturbance observer-based MEMS gyroscope combined learning control method

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Embodiment Construction

[0067] refer to figure 1 . The specific steps of the MEMS gyroscope compound learning control method based on the disturbance observer of the present invention are as follows:

[0068] (a) The dynamic model of the MEMS gyroscope considering the quadrature error is:

[0069]

[0070] 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.

[0071] 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...

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Abstract

The invention discloses a disturbance observer-based MEMS gyroscope combined learning control method, which is used for solving the technical problem that the modal control method of the existing MEMSgyroscope is poor in practicability. According to the technical scheme, the disturbance observer-based MEMS gyroscope combined learning control method comprises the following steps: firstly, designing a disturbance observer, estimating and compensating disturbance so as to reduce buffeting of a slip formwork; and according to fuzzy prediction errors and tracking error, designing the combined self-adaptive rule of fuzzy logic weight, correcting fuzzy logic weight coefficient, thus realizing the effective dynamic estimation of unknown dynamics. Considering the prediction error and tracking error, the effective dynamic estimation of unknown dynamics can be realized by designing the combined learning innovation rule of fuzzy logic weight, correcting fuzzy logic weight coefficient. By combining slip formwork control theory, the feedforward compensation on the unknown dynamics of the MEMS gyroscope can be realized, and the control precision of the MEMS gyroscope can be further improved. Thedisturbance observer is designed to compensate the disturbance in slip formwork control, so that the buffeting of the slip formwork can be reduced, and the practicability is good.

Description

technical field [0001] The invention relates to a mode control method of a MEMS gyroscope, in particular to a method for compound learning control of a MEMS gyroscope 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), J...

Claims

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Application Information

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