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Method for controlling flexible structure and self-adaptive changing structure by radial basis function (RBF) neural network

A technology of variable structure control and self-adaptive control, which is applied in the field of aerospace and aviation, can solve problems such as the high-precision control target of the vibration and attitude control system of solar panels, and achieve simple and easy control methods, fast training speed, The effect of simple structure

Inactive Publication Date: 2011-05-25
HARBIN INST OF TECH
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the contradiction between the vibration of the solar panel and the high-precision control target of the attitude control system in the existing method, and to provide a radial structure adaptive variable structure control using RBF neural network method

Method used

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  • Method for controlling flexible structure and self-adaptive changing structure by radial basis function (RBF) neural network
  • Method for controlling flexible structure and self-adaptive changing structure by radial basis function (RBF) neural network
  • Method for controlling flexible structure and self-adaptive changing structure by radial basis function (RBF) neural network

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specific Embodiment approach 1

[0025] Specific implementation mode one: the following combination figure 1 and figure 2 This embodiment will be described.

[0026] Down figure 1 To approximate the spacecraft model with flexible attachments, it consists of a central rigid body with a radius b and a uniform cantilever beam flexible attachment, and the flexible beams are symmetrically distributed. In the figure, OXZ and oxz are the inertial coordinate system and the body coordinate system respectively, oz coincides with the axis of the undeformed flexible attachment, and its origin is located at the connection between the flexible attachment and the central rigid body, which is used to describe the relative rotation relationship between the coordinate systems is the attitude angle. m is the mass of the tip, T is expressed as the external control torque, where the deformation at any point [0 l] is w(x, t).

[0027] In order to simplify the derivation of the dynamic model of the flexible spacecraft, the fol...

Embodiment approach 2

[0061] Specific embodiment two: this embodiment is a further description of the radial structure adaptive variable structure control method using the RBF neural network described in the specific embodiment one, and this embodiment is to the actual satellite attitude information x (t) and Desired satellite attitude information x m (t) for further clarification. The vector equation of the actual satellite attitude information x (t) is expressed as:

[0062] x · = Ax + Bu ( t ) + Bu is + Bd ( t ) ,

[0063] Among them, A and B are the first-order coefficients,

[0064] Expected satellite attitude information x output by nominal system 2 m The vector equation of (t) is expressed as:

[0065] x · m ...

Embodiment approach 3

[0067] Specifically, the third embodiment: This embodiment is a further description of the radial structure adaptive variable structure control method using the RBF neural network described in the first embodiment, and this embodiment is a further description of the error e(t).

[0068] The error e(t) described in this embodiment is obtained according to the following formula:

[0069] e(t)=x(t)-x m (t).

[0070] Among them, x(t) is the actual satellite attitude information, x m (t) is the desired satellite attitude information.

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Abstract

The invention provides a method for controlling a flexible structure and a self-adaptive changing structure by a radial basis function (RBF) neural network, belonging to the field of aviation. The method aims at solving the problem that the existing method can not preferably solve the conflict between the shake of a solar sailboard and the high-precision control target of an attitude control system. The method comprises the following steps: an E1 input forming module is used for converting an inputted expected satellite attitude angle theta d into a response uE1, and outputting the response uE1 to a nominal system and a flexible spacecraft; the nominal system is used for outputting expected satellite attitude information xm (t), and the flexible spacecraft is used for outputting practical satellite attitude information x (t) to obtain an error e (t) by comparing the xm (t) with the x (t); a sliding film face control module is used for obtaining a proper sliding film face s according to the error e (t), and transmitting the s to the RBF neural network and a self-adaptive locoregional control module; the self-adaptive locoregional control module is used for outputting a self-adaptive locoregional control u* to the RBF neural network; and the RBF neural network is used for obtaining and adjusting a locoregional control un and an adding result between the un and the uE1 according to the s and the u* to control the satellite attitude of the flexible spacecraft to achieve an expected value.

Description

technical field [0001] The invention relates to a radial structure self-adaptive variable structure control method using RBF neural network, which belongs to the field of aerospace. Background technique [0002] Due to the simplification of the modeling process of the spacecraft with flexible attachments and the complexity of the working environment of the spacecraft, the uncertainty of the spacecraft is very prominent, mainly in the following aspects: (1) The multi-flexible spacecraft itself is a For a distributed parameter system, the system state is a function of time and space, with infinite degrees of freedom. In engineering design, the hypothetical mode method is used to approximate the dynamic characteristics of flexible bodies, and the direct coupling between multiple flexible bodies is not considered in modeling; (2) During the entire flight process, due to fuel consumption , changes in the mass and center of mass of the spacecraft, coupled with the aging of compon...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 王岩雷拥军唐强闫晓军
Owner HARBIN INST OF TECH
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