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Robust adaptive spatial flexible system expansion control method based on neural network

A technology of robust self-adaptation and neural network, which is applied in the field of robust self-adaptive collaborative consistency of neural network, and can solve problems such as considering the state constraints of autonomous maneuvering units

Active Publication Date: 2018-07-24
NORTHWESTERN POLYTECHNICAL UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Among the existing patents, there is no related patent that considers the state constraints of the autonomous motorized unit when designing the control law of the autonomous motorized unit

Method used

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  • Robust adaptive spatial flexible system expansion control method based on neural network
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  • Robust adaptive spatial flexible system expansion control method based on neural network

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Embodiment Construction

[0058] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0059] Step 1. Establish the dynamic model of the flexible net and the autonomous motorized unit during deployment, and convert the dynamic model of the autonomous motorized unit into a form of state equation that is convenient for controller design. In this model, the autonomous motorized unit is simplified as a particle with only orbital motion and no attitude motion, and the four autonomous motorized units are located at the four corners of the flexible net. After the ejection, the flexible net only has parallel motion relative to the platform satellite, without relative rotation.

[0060] The coordinate system of the system is attached as figure 1 As shown, the coordinate system is defined as follows:

[0061] 1. The earth's equatorial inertial coordinate system EXYZ: the origin of the inertial coordinate system is the center of the earth, the axis Z is per...

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Abstract

The invention relates to a robust adaptive spatial flexible system expansion control method based on a neural network. The method comprises the steps that a dynamic model of a space fly-net robot suitable for the design of a controller is established; the controller input U of the dynamic model is designed under the condition that the state of autonomous maneuvering units is limited; for the designed controller, the stability of a closed-loop system is proved; and for the designed controller, the autonomous maneuvering units are proved to satisfy the state constraint. The method has the advantages that the actual condition of the state constraint, which is caused by tether connection, of the autonomous maneuvering units is considered; the robust adaptive distributed consistency control method based on the neural network is used to design the controller for the space fly-net robot during deployment under a bounded disturbance condition; four autonomous maneuvering units can achieve thedesired state while satisfying the state constraint; the synergy consistency of configuration is realized; the flutter of a flexible network is reduced; and a good flexible network type is maintained.

Description

technical field [0001] The invention belongs to the research on the space flexible system deployment control technology, and relates to a space flexible system deployment control method based on neural network robust self-adaption, and specifically relates to the realization of the desired configuration under the condition of limited state during the deployment process of the tethered spacecraft system Robust adaptive co-consistency for neural networks. Background technique [0002] The tethered spacecraft system is a space flexible robot system with a tether structure, which has strong adaptability and high safety, and will play an important role in space on-orbit service and maintenance. The space flying net robot system proposed in this patent is a typical space flexible robot system. [0003] The space flying net robot system is a special multi-agent system, and the main active units are connected by tethers, so that the relative state between the units is constrained. ...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 黄攀峰刘亚张帆孟中杰张夷斋刘正雄董刚奇
Owner NORTHWESTERN POLYTECHNICAL UNIV
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