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A method of deflection satellite adaptive neural network sliding gesture control method

A flexible satellite and neural network technology, applied in the field of flexible satellite adaptive neural network sliding mode attitude control, can solve problems such as reducing system stability, flexible satellite attitude fluctuation, etc., and achieve high attitude control accuracy and stability, Reduce chattering, good robustness

Active Publication Date: 2017-08-25
HARBIN INST OF TECH
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the attitude fluctuation caused by the modal vibration of the sailboard and the antenna rotation of the flexible satellite reduces the stability of the system and proposes a flexible satellite adaptive neural network sliding mode attitude control method

Method used

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  • A method of deflection satellite adaptive neural network sliding gesture control method
  • A method of deflection satellite adaptive neural network sliding gesture control method
  • A method of deflection satellite adaptive neural network sliding gesture control method

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specific Embodiment approach 1

[0021] Specific embodiment one: a kind of flexible satellite self-adaptive neural network sliding mode attitude control method of this embodiment is specifically prepared according to the following steps:

[0022] Step 1, establishing a satellite attitude model with a moving antenna; establishing a dynamic model of a flexible satellite attitude by using a mixed coordinate method;

[0023] Step 2. According to the attitude dynamics model of the flexible satellite, ignore the high-order coupling items related to the mode in the attitude dynamic equation of the flexible satellite, consider the inertial directional flight of the satellite, and adopt the small angle assumption at the same time to obtain the simplified flexible Satellite attitude dynamic equation;

[0024] Step 3, according to the simplified attitude dynamic equation of the flexible satellite, utilize the RBF neural network to design the sliding mode attitude controller;

[0025] Step 4, further adopting the RBF ne...

specific Embodiment approach 2

[0029] Specific embodiment two: the difference between this embodiment and specific embodiment one is: set up the satellite attitude model with moving antenna in the step one; Adopt mixed coordinate method to establish flexible satellite attitude dynamics model specifically as follows:

[0030] (1), the attitude dynamics equation containing two sailboards and a moving antenna has the following form (in the equation (2-1), the first is the rotation equation of the satellite body, and the second is the rotation equation of the antenna):

[0031]

[0032]

[0033] Among them, I s ∈ R 3×3 is the moment of inertia matrix of the star; ω s =[ω 1 ,ω 2 ,ω 3 ] T ∈ R 3 is the attitude angular velocity vector of the system relative to the inertial system and projected and decomposed in the system; ω 1 , ω 2 and ω 3 Respectively, the attitude angular velocity of the system relative to the inertial system and the projection decomposition of the X, Y and Z axes in the system; ...

specific Embodiment approach 3

[0038] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is that in step two, according to the dynamic model of the flexible satellite attitude, the high-order coupling items related to the mode in the dynamic equation of the flexible satellite attitude are ignored, Considering the inertial directional flight of the satellite, and adopting the assumption of a small angle, the specific process of the simplified attitude dynamic equation of the flexible satellite is obtained as follows:

[0039] (1) Neglecting the high-order coupling items related to the mode in the dynamic equation of the flexible satellite attitude, the dynamic model of the flexible satellite attitude is simplified as:

[0040]

[0041] In the formula,

[0042]

[0043]

[0044]

[0045] D is the sum of interference and uncertainty, and D is bounded; F is an unknown nonlinear term;

[0046] (2) Considering the inertial directional flight of the sa...

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Abstract

A flexible satellite adaptive neural network sliding mode attitude control method relates to a flexible satellite adaptive neural network sliding mode attitude control method. The invention is a flexible satellite adaptive neural network sliding mode attitude control method proposed to solve the problem of the attitude fluctuation of the flexible satellite due to the modal vibration of the sail board and the rotation of the antenna, and to reduce the stability of the system. In the method, the first step is to establish a flexible satellite attitude dynamics model; the second step is to obtain a simplified flexible satellite attitude dynamics equation; and the third step is to use the RBF neural network according to the simplified flexible satellite attitude dynamics equation. Design the sliding mode attitude controller; step 4, further use the RBF neural network to approximate the symbolic function η'sgn(s) to weaken the influence of chattering on the sliding mode attitude controller; obtain the sliding mode attitude controller after the chattering is weakened, etc. realized. The invention is applied to the field of flexible satellite attitude control.

Description

technical field [0001] The invention relates to an attitude control method, in particular to a flexible satellite self-adaptive neural network sliding mode attitude control method. Background technique [0002] As the functions and types of satellites increase, the structure of satellites becomes very complex and their sizes become larger. It is usually necessary to install flexible accessories to realize various functions on the star body, among which the application of solar panels and sports antennas is the most common. Such satellites with flexible accessories are collectively called flexible satellites. The existence of these flexible accessories makes the attitude control system of the satellite have the characteristics of nonlinearity and parameter uncertainty, which puts forward higher requirements for the attitude control of the satellite. How to make the satellite attitude control system have excellent performances such as stability and rapidity while suppressing ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
Inventor 孙延超马广富李传江张超王鹏宇姜丽松
Owner HARBIN INST OF TECH
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