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Neural network control method for mems gyroscope parameter identification based on non-singular terminal sliding mode design

A neural network control, non-singular terminal technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problem of long adjustment time and achieve the effect of fast drive control

Active Publication Date: 2022-03-29
NORTHWESTERN POLYTECHNICAL UNIV
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  • Application Information

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Problems solved by technology

[0005] In order to overcome the problem of too long adjustment time of the drive control system in the prior art, the present invention proposes a MEMS gyroscope parameter identification neural network control method based on non-singular terminal sliding mode design

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  • Neural network control method for mems gyroscope parameter identification based on non-singular terminal sliding mode design
  • Neural network control method for mems gyroscope parameter identification based on non-singular terminal sliding mode design
  • Neural network control method for mems gyroscope parameter identification based on non-singular terminal sliding mode design

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Embodiment Construction

[0074] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0075] The invention discloses a MEMS gyroscope parameter identification neural network control method based on non-singular terminal sliding mode design, combining figure 1 , the specific design steps are as follows:

[0076] (a) The MEMS gyroscope dynamics model considering the existence of orthogonal error and system uncertainty is:

[0077]

[0078] Among them, m is the mass of proof mass, Ω z Enter the angular velocity for the gyro, and x * are the acceleration, velocity and displacement of the MEMS gyroscope proof mass along the drive axis, respectively, and y * are the acceleration, velocity and displacement along the detection axis, respectively, and is the electrostatic driving force, c xx and c yy is the damping coefficient, k xx and k yy is the stiffness coefficient, and is the nonlinear coefficient, c xy and c yx is the damping...

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Abstract

The invention relates to a MEMS gyroscope parameter identification neural network control method based on non-singular terminal sliding mode design, and belongs to the field of intelligent instruments. This method transforms the gyroscope dynamics model into a dimensionless dynamics linear parameterized model; designs a dynamics parallel estimation model, constructs the system prediction error, and designs a compound learning law in combination with the tracking error to effectively estimate the system uncertainty caused by environmental changes ; Based on the tracking error and prediction error, the dynamic parameter adaptive law is designed to realize parameter identification; the non-singular terminal sliding mode controller is designed to realize the fast driving control of the gyroscope. The MEMS gyroscope parameter identification neural network control method based on non-singular terminal sliding mode design designed by the present invention can solve the problem of too long adjustment time of the drive control system, realize fast drive control of the gyroscope, and identify dynamic parameters at the same time, further improving the MEMS gyroscope instrument performance.

Description

technical field [0001] The invention relates to a driving control method of a MEMS gyroscope, in particular to a MEMS gyroscope parameter identification neural network control method based on a non-singular terminal sliding mode design, and belongs to the field of intelligent instruments. Background technique [0002] In practical engineering applications, changes in the working environment of MEMS gyroscopes such as temperature, air pressure, magnetic field, and vibration bring challenges to gyroscope drive control, especially for controllers that lack adaptive capabilities to adapt to dynamically changing environments. At present, two commonly used solutions are: (1) improve the hardware design, increase the isolation components to shield the influence of the external environment; (2) improve the controller design scheme, and enhance the self-adaptive ability of the controller. [0003] Since the sliding mode control is not sensitive to changes in the external environment ...

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
Owner NORTHWESTERN POLYTECHNICAL UNIV