Performance limited flexible manipulator control method based on determining learning theory

A technology that determines the learning theory and flexible manipulators. It is applied in the direction of manipulators, program-controlled manipulators, and manufacturing tools. It can solve the problems of time-consuming redundancy and difficult access to neural networks.

Active Publication Date: 2016-11-09
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In order to solve the time-consuming and redundant online adjustment process of the neural network, the weights of the neural network need to converge eventually, but this is very difficult to achieve

Method used

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  • Performance limited flexible manipulator control method based on determining learning theory
  • Performance limited flexible manipulator control method based on determining learning theory
  • Performance limited flexible manipulator control method based on determining learning theory

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Experimental program
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Embodiment

[0048] This embodiment mainly studies the trajectory tracking control of the flexible manipulator in the case of limited tracking performance. figure 1 A schematic diagram of the flexible robotic arm system.

[0049] The overall control block diagram of the performance-limited flexible manipulator control method based on deterministic learning theory is as follows: figure 2 As shown, its detailed implementation process includes:

[0050] Step (1): Establish a dynamic model of the flexible manipulator.

[0051] According to the following flexible manipulator system model:

[0052] I x ·· 1 + M g L sin x 1 + K ...

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Abstract

The invention discloses a performance limited flexible manipulator control method based on determining learning theory. Aiming at the indeterminacy of the dynamic model of the flexible manipulator, the method designs a tracking error to satisfy the limitation of constraint conditions, and forms an error controller. The method in the invention comprises the following steps: building a dynamic model of the flexible manipulator, building a system state observer, designing tracking error performance constraint conditions, designing a neural network controller based on the determining learning theory, and correcting the controller utilizing experiential knowledge. The method designed in the invention can realize the dynamic properties of rapid convergence and low overshoot, satisfy the limitation of set constraint conditions, avoid the on-line regulations to the neural network weights at the same time, and shorten the control time. In addition, the method can utilize the learned experiential knowledge to control the later same task rapidly.

Description

technical field [0001] The invention belongs to the field of trajectory tracking control of flexible manipulators, in particular, aiming at the uncertainty of the dynamic model of the flexible manipulator system, the tracking error is designed so as to satisfy constraints. A performance-constrained flexible manipulator control method based on deterministic learning theory is presented. Background technique [0002] Nowadays, with the development of robots in the direction of high precision and speed, mechanical components are becoming more and more lightweight. Compared with traditional rigid manipulators, flexible manipulators have the characteristics of light structure, large working space and high efficiency, so flexible components are more and more widely used in manufacturing, aerospace and other fields, but the flexibility brought by the flexible arm The effect will lead to mechanical vibration, which will make it more difficult to achieve the stability and accuracy r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
CPCB25J9/1635B25J9/1664
Inventor 王敏杨安乐方冲
Owner SOUTH CHINA UNIV OF TECH
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