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A neural network control system and method for manipulator with disturbance observer

A technology of neural network control and disturbance observer, which is applied in the direction of general control system, control/regulation system, program control, etc., and can solve problems such as high accuracy requirements

Active Publication Date: 2018-10-16
TAIZHOU UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, methods such as adaptive control and robust control have higher requirements on the accuracy of the dynamic model of the manipulator.

Method used

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  • A neural network control system and method for manipulator with disturbance observer
  • A neural network control system and method for manipulator with disturbance observer
  • A neural network control system and method for manipulator with disturbance observer

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Embodiment Construction

[0089] The present invention will be further elaborated below by describing a preferred specific embodiment in detail in conjunction with the accompanying drawings.

[0090] Such as figure 1 As shown, a manipulator neural network control system with a disturbance observer, the control system includes: a first adder 1, a RBF neural network operator 3 (Radical Basis Function, RBF for short), a second An addition unit 2 , a calculation torque controller 4 , a third addition unit 7 , a manipulator system 5 and a disturbance observer 6 .

[0091] Wherein, the first input terminal of the first adder 1 inputs the desired motion displacement signal q of the manipulator system 5 d ; The first input terminal of RBF neural network operator 3 is connected with the output terminal of the first adding operator 1; The output end of this second addition operator 2 is connected with the second input end of RBF neural network operator 3; The first input end of calculation torque controller 4...

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Abstract

The invention discloses a manipulator nerve network control system with an interference observer and a control method. The manipulator nerve network control system with the disturbance observer is established by a first addition arithmetic unit, an RBF nerve network arithmetic unit, a second addition arithmetic unit, a calculating torque controller, a third addition arithmetic unit, a manipulator system, and a disturbance observer to handle the dynamic uncertain items in a manipulator system and external disturbance. The RBF nerve network arithmetic unit is used for approximating to the dynamic uncertain items caused by the uncertain dynamics parameters of the manipulator system, and the disturbance observer estimates and compensates the external disturbance. The manipulator nerve network control system also can verify the effectiveness of the control method on the dynamic uncertain items and the external disturbance. The manipulator nerve network control system can effectively improve the control performance and the tracking precision of the manipulator system.

Description

technical field [0001] The invention relates to a manipulator control system and a control method, in particular to a manipulator neural network control system and method with a disturbance observer. Background technique [0002] The manipulator is a very complex multi-input multi-output nonlinear system, and there are inevitably various uncertainties. It is impossible to obtain an accurate dynamic model of the system, and its control is very complicated. From the inside of the system, due to the inaccurate measurement and modeling, it is difficult to know the parameters of the dynamic model, such as the mass and length of each connecting rod of the robot; from the outside, the system will also be subject to load changes and the effects of various unpredictable disturbances. Therefore, in view of the parameter uncertainty and external disturbance in the manipulator, it is necessary to design an appropriate control scheme to ensure the robustness of the system. [0003] In ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042G05B2219/32335G05B2219/33004
Inventor 王三秀陈跃陈光苏娜
Owner TAIZHOU UNIV