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Neural network inversion control method for flexible manipulator system

A technology of flexible manipulator and neural network, applied in the field of neural network control

Active Publication Date: 2015-09-30
GUANGZHOU ETON ELECTROMECHANICAL
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Because of the uncertain factors of these parameters, it is more challenging to design the corresponding controller

Method used

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  • Neural network inversion control method for flexible manipulator system
  • Neural network inversion control method for flexible manipulator system
  • Neural network inversion control method for flexible manipulator system

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Embodiment Construction

[0087] The present invention will be further described below in conjunction with the accompanying drawings.

[0088] refer to Figure 1-Figure 5 , a neural network inversion control method for a flexible manipulator system, comprising the following steps:

[0089] Step 1, establish the dynamic model of the servo system of the manipulator, the process is as follows:

[0090] 1.1 The expression form of the dynamic model of the manipulator servo system is

[0091] I q ·· + K ( q - θ ) + M g L sin ...

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Abstract

The invention discloses a neural network inversion control method for a flexible manipulator system. The neural network inversion control method comprises the following steps of establishing a dynamic model of a flexible manipulator servo system and performing equivalent transformation on the dynamic model, and initializing a system state, sampling time and a control parameter; introducing a virtual control variable into the design of each step by combining sliding-mode control and an inversion method, and finally deducing self-adapting controller input; calculating the tracking error, the integral sliding mode surface, the error variable and the differential of a control system. Meanwhile, by utilizing the approximation characteristic of a neural network, the complexity explosion problem brought by the inversion method and the approximation of model parameter uncertainty are avoided; the invention provides the neural network inversion control method capable of effectively improving the location tracking control performance of the flexible manipulator servo system, therefore the stable and rapid tracking of the system is realized.

Description

technical field [0001] The invention relates to a neural network control method for a flexible manipulator system, in particular to a neural network inversion control method for a flexible manipulator system with an uncertain model. Background technique [0002] The servo system of the manipulator has been widely used in high-performance systems such as robots and aviation vehicles. How to realize the fast and precise control of the servo system of the manipulator has become a hot issue. However, rigid manipulator systems often do not consider the flexibility of the joints, which often leads to reduced efficiency or even failure of the control system. In order to improve the tracking control performance, it is necessary to consider the flexible manipulator model. The flexible mechanical arm is to add the spring stiffness coefficient between the joints. Therefore, a more complex structural motion equation is introduced into the system model, which makes the control more diff...

Claims

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Application Information

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IPC IPC(8): G05B13/04
Inventor 陈强施琳琳
Owner GUANGZHOU ETON ELECTROMECHANICAL
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