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Cantilever beam vibration control method on basis of self-adaption neural network control

A technology of neural network control and cantilever beam, applied in adaptive control, general control system, control/regulation system, etc., can solve problems such as model uncertainty, parameter perturbation and external disturbance force

Inactive Publication Date: 2014-12-24
HOHAI UNIV CHANGZHOU
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Problems solved by technology

[0006] The purpose of the present invention is to overcome the defects existing in the existing cantilever beam vibration control method, especially to improve the tracking performance of the cantilever beam system to the ideal trajectory under various interference conditions such as model uncertainty, parameter perturbation, and external disturbance force. and the robustness of the whole system, and provide a cantilever beam vibration control method based on adaptive neural network control

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  • Cantilever beam vibration control method on basis of self-adaption neural network control
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  • Cantilever beam vibration control method on basis of self-adaption neural network control

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Embodiment Construction

[0055] In order to further illustrate the technical means and effects adopted by the present invention to achieve the intended invention purpose, the present invention will be described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0056] The vibration control principle of a cantilever beam based on adaptive neural network control of the present invention is as follows: figure 1 As shown, it includes the following parts:

[0057] (1) Establish a filter error model based on cantilever beam

[0058]The vector form of the cantilever beam dynamics model:

[0059] q . . + C q . + Kq = u + d - - - ( 1 )

[0060] where C,K∈R i*i is the system parameter, where C is the damping...

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Abstract

The invention discloses a cantilever beam vibration control method on the basis of self-adaption neural network control and is designed on the basis of filtered tracking error. A controller comprises proportional differential items and RBF neural network items. By the cantilever beam vibration control method, with unknown functions of a cantilever beam system of an RBF neural network approach, an updating algorithm of the weight of the RBF neural network is designed on the basis of Lyapunov stability theory, and overall stability of the system is guaranteed. Robust items are added into the updating algorithm, boundedness of control input is guaranteed, and the final tracking error is kept within any small range by the aid of proportional differential control items. Under the conditions of no structural or nonstructural parameters of a cantilever and with external interference, the control method is capable of accurately tracking and controlling the cantilever system, and robustness and reliability of the system are improved.

Description

technical field [0001] The invention relates to a vibration control method of a cantilever beam based on adaptive neural network control, and belongs to the technical field of cantilever beam control. Background technique [0002] A cantilever beam means that one end of the beam is a fixed support that does not produce axial, vertical displacement and rotation, and the other end is a free end (which can generate forces parallel to and perpendicular to the axial direction). In the force analysis of engineering mechanics, it is a typical simplified model. In actual engineering analysis, most of the actual engineering stress components can be simplified as cantilever beams. [0003] With the rapid development of science and technology, the rapid development of aerospace technology and the increasing scale of space activities, the requirements for aerospace technology and space structures are becoming more and more stringent. A large number of space structures, such as large mo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 胡桐月费峻涛
Owner HOHAI UNIV CHANGZHOU
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