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Recursive fuzzy neural network nonsingular terminal sliding mode control method of micro gyroscope

A fuzzy neural network, non-singular terminal technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the complex debugging, reduce the sensitivity and accuracy of the gyroscope system, and the characteristics of the original are easily affected by environmental changes and other problems to achieve the effect of ensuring the driving frequency

Active Publication Date: 2020-01-17
HOHAI UNIV CHANGZHOU
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Problems solved by technology

However, there are certain errors in the production and processing of the micro gyroscope, and its original characteristics are easily affected by environmental changes. These factors will reduce the sensitivity and accuracy of the gyroscope system
After decades of research, although micro-gyroscopes have made significant progress in structural design, due to the limitations of environmental interference and manufacturing errors, it is difficult to make a qualitative leap in the development of micro-gyroscopes.
[0003] The micro gyroscope control method commonly used at present needs to solve the problem of stable control of the oscillation amplitude and frequency of the drive shaft and the matching of the frequency of the two axes, but the traditional method often has the disadvantages of poor immunity, low flexibility, and complicated debugging. In the traditional control process, the actual damping coefficient, stiffness coefficient and other parameters of the micro gyroscope are often not accurately obtained.
These defects make the traditional micro gyroscope control method difficult to apply in high-precision occasions

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  • Recursive fuzzy neural network nonsingular terminal sliding mode control method of micro gyroscope
  • Recursive fuzzy neural network nonsingular terminal sliding mode control method of micro gyroscope
  • Recursive fuzzy neural network nonsingular terminal sliding mode control method of micro gyroscope

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0048] 1. Mathematical model of micro gyroscope:

[0049] A micro gyroscope usually consists of three parts: a mass suspended by an elastic material support, an electrostatic drive device, and a sensing device. This can be simplified as figure 1 The shown is a damped oscillation system composed of a mass block and a spring. According to the Coriolis effect, when the mass block m is in simple harmonic motion driven by a periodic electrostatic force, if the z-axis detects the input from the angular velocity Ω, The mass will vibrate on the Y axis. Considering that the angular velocity in the z-axis direction of the micro-gyroscope will produce dynamic coupling between the X-axis and the Y-axis, ...

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Abstract

The invention discloses a novel recursive fuzzy neural network nonsingular terminal sliding mode control method of a micro gyroscope system. The recursive fuzzy neural network nonsingular terminal sliding mode control method comprises the steps of: designing a nonsingular terminal sliding mode surface function of the micro gyroscope system; determining a nonsingular terminal sliding mode control rate added into the nonsingular terminal sliding mode surface function based on a first Lyapunov stability criterion function; and replacing an uncertain item in the nonsingular terminal sliding mode control rate with output of a constructed recursive fuzzy neural network, and constructing a final control rate according to a result output by means of the constructed recursive fuzzy neural network and the nonsingular terminal sliding mode control rate based on a second Lyapunov stability criterion function, so as to realize tracking control over the micro gyroscope system. The nonsingular terminal sliding mode control adopted by recursive fuzzy neural network nonsingular terminal sliding mode control method has the advantages of high control precision and high robustness, and the singular problem existing in terminal sliding mode control is avoided; and parameters of the novel recurrent fuzzy neural network can be automatically stabilized to the optimal value according to a designed adaptive algorithm, so that the parameter training time is shortened, and the universality of the network structure is enhanced.

Description

technical field [0001] The invention relates to a control method of a micro gyroscope, in particular to a recursive fuzzy neural network non-singular terminal sliding mode control method of the micro gyroscope. Background technique [0002] Micro gyroscope is a basic measurement element that is often used in inertial navigation and inertial guidance systems. Due to its advantages of small size, low cost and high reliability, micro gyroscopes are widely used in military and civilian fields such as navigation and positioning of aviation, aerospace, navigation and land vehicles, and oilfield exploration and development. However, there are certain errors in the production and processing process of the micro gyroscope, and the characteristics of its original components are easily affected by environmental changes. These factors will reduce the sensitivity and accuracy of the gyroscope system. After decades of research, although micro-gyroscopes have made remarkable progress in s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 王哲费峻涛
Owner HOHAI UNIV CHANGZHOU
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