Adaptive neural network nonsingular terminal sliding mode control method for micro gyroscope

A non-singular terminal and neural network technology is applied in the field of non-singular terminal synovial control of micro-gyroscope adaptive neural network, which can solve the problems of reducing the sensitivity and accuracy of micro-gyroscope, reducing system chattering, and easy fluctuation of parameter system parameters.

Inactive Publication Date: 2016-09-07
HOHAI UNIV CHANGZHOU
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Problems solved by technology

However, due to the existence of errors in the manufacturing process and the influence of the external environment temperature, the difference between the characteristics of the original and the design is caused, resulting in the coupling stiffness coefficient and damping coefficient, which reduces the sensitivity and accuracy of the micro gyroscope.
In addition, the gyroscope itself is a multi-input multi-output system, and there is uncertainty in the parameters and the system parameters are easy to fluctuate under external disturbances. Therefore, reducing system chattering has become one of the main problems in the control of micro gyroscopes.

Method used

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  • Adaptive neural network nonsingular terminal sliding mode control method for micro gyroscope
  • Adaptive neural network nonsingular terminal sliding mode control method for micro gyroscope
  • Adaptive neural network nonsingular terminal sliding mode control method for micro gyroscope

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Embodiment

[0098] Go to step one:

[0099] refer to figure 1 As shown, a general micro gyroscope is composed of the following parts: a mass block, support springs along the X and Y axis directions, an electrostatic drive device and an induction device, wherein the electrostatic drive device drives the mass block to vibrate along the direction of the drive axis, and the induction device The displacement and velocity of the mass in the direction of the detection axis can be detected.

[0100] Then, the mathematical model of the micro-gyroscope established in step 1 is:

[0101] m x ·· + d x x x · + ...

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Abstract

The invention discloses an adaptive neural network nonsingular terminal sliding mode control method for a micro gyroscope. The method includes the steps of the establishing a mathematical model of the micro gyroscope, approximating the sum of the dynamic characteristics and external disturbance of the micro gyroscope by using a neural network control method, designing an adaptive neural network nonsingular terminal sliding mode device based on a dynamic surface; and controlling the micro gyroscope by using the adaptive neural network nonsingular terminal sliding mode device based on the dynamic surface. Through the method, a micro gyroscope system can rapidly reach a stable state, and manufacturing error and environment interference can be compensated. The algorithm designed based on dynamic surface method reduces parameters introduced, simplifies calculation and minimizes buffeting. Meanwhile, a nonsingular terminal sliding mode is introduced in the method to ensure that the system state converges in the sliding phase for a finite time and the control rules have no negative exponential terms, so that the effectiveness of the system can be improved.

Description

technical field [0001] The invention relates to the technical field of micro-gyroscope dynamic control, in particular to a non-singular terminal synovium control method based on a dynamic surface micro-gyroscope self-adaptive neural network. Background technique [0002] Micro gyroscope is widely used in the navigation and positioning of aviation, aerospace, navigation and land vehicles, as well as oilfield exploration and development, and other military and civilian fields to measure the angular velocity of inertial navigation and inertial guidance systems. Compared with traditional gyroscopes, micro gyroscopes have huge advantages in size and cost. However, due to the existence of errors in the manufacturing process and the influence of the external environment temperature, the difference between the characteristics of the original and the design is caused, resulting in the coupling stiffness coefficient and damping coefficient, which reduces the sensitivity and accuracy o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 雷单单曹頔王腾腾费峻涛
Owner HOHAI UNIV CHANGZHOU
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