Neural network-based servo control system and method

A technology of servo system and neural network, applied in general control system, control/adjustment system, control using feedback, etc., can solve the problems of low control precision, poor adaptability, unsuitable for high-precision control, etc., and achieve high control precision, The effect of ensuring stability and design work convenience

Inactive Publication Date: 2011-05-11
BEIHANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this traditional control method has poor adaptability, and the control accuracy is low when the system is disturbed, so it is not suitable for high-precision control occasions.

Method used

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  • Neural network-based servo control system and method
  • Neural network-based servo control system and method
  • Neural network-based servo control system and method

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Embodiment Construction

[0039] The theoretical structure of the servo control system according to an embodiment of the present invention is as follows figure 2 shown. The control part of the system includes a position loop controller 101 , an adaptive controller 102 , a neural network controller 104 , and a robust term part 105 .

[0040] figure 2 Reference numeral 107 in represents the control object of the servo control system. The most basic part of the control object is the servo execution part 1071 . In actual situations, the control object 107 may also generally include a current feedback part 1072 and a power amplification part 1073 .

[0041] figure 2 The servo control system of the illustrated embodiment also includes a position detection device 108 , a speed detection device 109 and a differentiator 106 .

[0042] 1) Position loop controller 101

[0043] The input of the position loop controller 101 is the difference between the position command and the position output, and its out...

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Abstract

The invention aims to improve the control accuracy of a servo system and provides a neural network model reference adaptive control method applied to the servo system. The nonlinearity of the servo system is effectively compensated, the interference is suppressed, and the tracking accuracy and robustness of the servo system are improved. In addition, the control of the servo system is not needed to be constructed on the basis of accurately modeling an object, the modeling cost is saved, the method is easily implemented in engineering, and the cost is reduced.

Description

technical field [0001] The invention relates to a neural network-based servo control system and method. technical background [0002] The servo system is a complex electromechanical control system, and its essence can be regarded as a position closed-loop control system driven by a motor, which plays an important role in national production and national defense construction. Because it occupies a very important position in various fields, the requirements for its performance are constantly increasing, especially in cutting-edge fields such as national defense, military and aerospace. It can be seen from the general development trend of servo systems at home and abroad that "high response, ultra-low speed, and high precision" are its main development directions. Among them, "high frequency response" reflects the ability of the servo system to track high-frequency signals, that is, the system's tracking ability when the position command signal is constantly changing. "Ultra-...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D3/12G05B13/02
Inventor 扈宏杰王林战平王希洋吕博
Owner BEIHANG UNIV
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