Unlock instant, AI-driven research and patent intelligence for your innovation.

Non-singular terminal sliding mode design-based MEMS gyroscope parameter identification neural network control method

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 so on

Active Publication Date: 2019-11-15
NORTHWESTERN POLYTECHNICAL UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Non-singular terminal sliding mode design-based MEMS gyroscope parameter identification neural network control method
  • Non-singular terminal sliding mode design-based MEMS gyroscope parameter identification neural network control method
  • Non-singular terminal sliding mode design-based MEMS gyroscope parameter identification neural network control method

Examples

Experimental program
Comparison scheme
Effect test

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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a non-singular terminal sliding mode design-based MEMS gyroscope parameter identification neural network control method, and belongs to the field of intelligent instruments and apparatuses. According to the method, a gyroscope dynamic model is converted into a dimensionless dynamic linear parameterized model; a dynamic parallel estimation model is designed, a system prediction error is constructed, and a tracking error design compound learning law is combined to effectively estimate the system uncertainty caused by environment change; a dynamic parameter adaptive law is designed on the basis of the tracking error and the prediction error so as to realize parameter identification; and a non-singular terminal sliding mode controller is designed to realize rapid driving control of a gyroscope. The non-singular terminal sliding mode design-based MEMS gyroscope parameter identification neural network control method is capable of solving the problem that the drivingcontrol system adjusting time is too long, realizing the rapid driving control of the gyroscopes, identifying the dynamic parameters and further improving the MEMS gyroscope 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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 许斌张睿
Owner NORTHWESTERN POLYTECHNICAL UNIV