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Learning control method of small-sized industrial mechanical arm

An industrial manipulator, learning control technology, applied in manipulators, program control manipulators, manufacturing tools, etc.

Inactive Publication Date: 2017-07-21
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are few mature and effective control methods for such small industrial manipulators driven by steering gears.

Method used

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  • Learning control method of small-sized industrial mechanical arm
  • Learning control method of small-sized industrial mechanical arm
  • Learning control method of small-sized industrial mechanical arm

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Experimental program
Comparison scheme
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Embodiment Construction

[0028] The present invention will be further elaborated and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical features of the various implementations in the present invention can be combined accordingly on the premise that there is no conflict with each other.

[0029] figure 1 It is a flowchart of a learning control method for a small industrial manipulator proposed by the present invention. In order to conveniently illustrate the features and advantages of the present invention, the specific steps of the present invention will be described below in combination with simulation experiments.

[0030] In the simulation experiment, a manipulator with 5 degrees of freedom is used as the controlled object. figure 2 is the actual structure of the 5-DOF manipulator. The mathematical description of the manipulator is shown in (1) formula.

[0031]

[0032] In the formula (1), the subscript n represents the execution of the ...

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Abstract

The invention discloses a learning control method of a small-sized industrial mechanical arm. According to the learning control method of the small-sized industrial mechanical arm, for specific repetitive tasks, after an expected operation path of the mechanical arm is obtained, an expected change path of each joint angle is calculated according to known parameters of a mechanical arm model; in the process of executing the task once, an initial control signal is corrected in real time according to the difference between the actual joint angle and an expected joint angle and set to be the initial control signal of the next-time task; and by means of the actual paths, measured in the task executing process, of tongs and all joint angles, the parameters of the mechanical arm model are updated through a parameter estimation method, and then the process is repeatedly executed. By the adoption of the learning control method, the mechanical arm can rapidly complete automatic tracking of the expected path during processing the repetitive tasks; in addition, the parameter estimation method is adopted, the automatic control problem existing when a mechanical arm model is inaccurate is effectively solved, and the requirement, for the precision of the mechanical arm model, of a control system is greatly lowered.

Description

technical field [0001] The invention belongs to the field of automatic control of manipulators, in particular to a learning control method for small industrial manipulators. Background technique [0002] In the production of light and handicraft industries, there are a lot of manual labor with high repetition, high intensity and low technical content. With the decline of my country's fertility rate and the deepening of the aging trend in recent years, the total number of labor force in my country has declined, and labor costs have increased year by year. The economic benefits brought by "machine replacement" to enterprises will become more and more obvious. The role of industrial manipulators in the production process of light and handicraft industries cannot be ignored. [0003] In industries such as automobile manufacturing and electronics industry, industrial manipulators and their supporting control methods have been widely used and matured; however, most of the existin...

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/163
Inventor 宋春跃林清钊
Owner ZHEJIANG UNIV