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Flexible satellite adaptive neural network sliding mode attitude control method

A flexible satellite and neural network technology, which is applied in the field of flexible satellite adaptive neural network sliding mode attitude control, can solve the problems of flexible satellite attitude fluctuations and reduce system stability, and achieve weakening buffeting, attitude control accuracy and High stability and good robustness

Active Publication Date: 2015-09-09
HARBIN INST OF TECH
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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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  • Flexible satellite adaptive neural network sliding mode attitude control method
  • Flexible satellite adaptive neural network sliding mode attitude control method
  • Flexible satellite adaptive neural network sliding mode attitude 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 a satellite attitude model with a moving antenna in step one; adopt the hybrid coordinate method to establish a 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] I s ω · s + ω s × I s ω s + Σ k ( F sk η · ...

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] ω · s = F + Gu + D - - - ( 2 - ...

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Abstract

Provided is a flexible satellite adaptive neural network sliding mode attitude control method. The invention relates to a flexible satellite adaptive neural network sliding mode attitude control method. The invention provides a flexible satellite adaptive neural network sliding mode attitude control method to solve the problem that the attitude of a flexible satellite fluctuates due to modal vibration of a panel and rotation of an antenna and the reduction of system stability is caused thereby. The method comprises the following steps: step 1, establishing a flexible satellite attitude dynamics model; step 2, obtaining a simplified flexible satellite attitude dynamics equation; step 3, designing a sliding mode attitude controller with use of an RBF neural network according to the simplified flexible satellite attitude dynamics equation; and step 4, further using an RBF neural network approximation sign function eta'sgn(s) to weaken the influence of buffeting to the sliding mode attitude controller so as to obtain a buffeting-weakened sliding mode attitude controller. The flexible satellite adaptive neural network sliding mode attitude control method of 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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IPC IPC(8): G05B13/04
Inventor 张超孙延超王鹏宇姜丽松马广富李传江
Owner HARBIN INST OF TECH
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