Neural network control-based reload robot position controller

A neural network control and neural network technology, which is applied in the field of heavy-duty robot position controllers, can solve the problems that the single-input and single-output linear control method cannot meet the application requirements, and achieve the simplification of learning rules, ensure the convergence speed, and improve performance. Effect

Inactive Publication Date: 2015-04-08
NANJING PANDA ELECTRONICS +1
View PDF6 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is that the traditional single-input single-output linear control method

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Neural network control-based reload robot position controller
  • Neural network control-based reload robot position controller
  • Neural network control-based reload robot position controller

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] The implementation method of the present invention will be described below in conjunction with the accompanying drawings. The heavy-duty robot position controller combined with neural network control of the present invention includes a neural network controller and several servo controllers.

[0022] Each servo drive includes a position controller, a speed controller and a current controller.

[0023] The neural network controller outputs several position, speed and current control signals to each servo controller. The driving signal of each servo drive is fed back to the neural network controller, wherein the feedback signal includes position feedback signal, speed feedback signal and current feedback signal. Each servo driver drives a servo motor, the servo motor will feed back the position signal and current signal to the servo driver through its encoder, and then the servo driver will feed back the position signal and current signal to the neural network controller...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

A neural network control-based reload robot position controller comprises a neural network controller and a plurality of servo drivers. The neural network controller provides control information for the servo drivers. Each servo driver comprises a speed controller, a position controller and a current controller. The neural network controller adopts an Elman network in a dynamic recursive neural network structure to overcome the dynamic system identification problems, guarantee convergence rate and simplify learning rule method. An input layer is connected with the output of a sensor, and input information including position, speed and current signals is detected and controlled through the sensor. The Elman network improves local feedback and self-feedback elements in the self-learning manner, thus the robot control network is imparted a memory function to adapt to complicated dynamic environment.

Description

technical field [0001] The invention relates to a position controller for a heavy-duty robot combined with neural network control, which belongs to the field of robot automation control. Background technique [0002] Today, with the continuous and deep integration of industrialization and informatization, the manufacture of large-scale equipment requires the participation of heavy-duty robots. The heavy-duty robot can grab and place the workpiece according to the predetermined requirements to complete repetitive work, so as to reduce the labor intensity of workers, improve work efficiency, and promote the automation of industrial production. [0003] The heavy-duty robot is a highly nonlinear, strongly coupled multiple-input multiple-output system. There are many unknown factors and the complexity of the robot itself, so that its positioning and motion trajectory during work may be quite different from the theoretical value, which affects the work performance, so controllin...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): B25J9/18G06N3/02
Inventor 付磊王富林何杏兴徐晗
Owner NANJING PANDA ELECTRONICS
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap