Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

The optimal control method of reconstructable robot decentralized nerves based on judging identification structure

A technology for reconfiguring robots and optimal control, applied in adaptive control, general control systems, control/regulation systems, etc., can solve the problem of low accuracy of decentralized optimal control, reduce computational burden, and reduce steady-state errors , the effect of reducing energy loss

Active Publication Date: 2021-11-30
CHANGCHUN UNIV OF TECH
View PDF13 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problem of low precision of decentralized optimal control in the prior art, the present invention proposes a method for optimal control of decentralized nerves of reconfigurable robots based on judgment and identification structure

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
  • The optimal control method of reconstructable robot decentralized nerves based on judging identification structure
  • The optimal control method of reconstructable robot decentralized nerves based on judging identification structure
  • The optimal control method of reconstructable robot decentralized nerves based on judging identification structure

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0102] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0103] Such as figure 1 As shown, according to the controller parameters and expected dynamic information, combined with the expected position variable, joint output torque and friction parameter estimates, the model compensation control law u based on local dynamic information is obtained i1 . Determine the initial value of the neural network, obtain the update rate of the weight of the neural network, obtain the identification error function, and obtain the neural network control law u of the identification strategy i2 . By approximating the cost function and evaluating the network, the neural optimal control law based on adaptive dynamic programming is obtained put u i1 , u i2 and Adding together, the optimal control law of distributed nerves is obtained, which is applied to the dynamic model to obtain the joint position variables. The position er...

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

The decentralized neural optimal control method for reconfigurable robots based on the evaluation and identification structure belongs to the field of robot control algorithms. In order to solve the problem of low accuracy of decentralized optimal control in the prior art, this method first establishes a dynamic model of the reconfigurable robot system , followed by constructing the cost function and the HJB equation, and finding the solution of the HJB equation through a learning algorithm based on policy iteration, and then through the identification of the coupling torque cross-linking items between the joint subsystems of the reconfigurable robot, and then using the neural network to The cost function is approximated, and finally the effectiveness of the proposed control method is verified by simulation; the present invention solves the problem of low accuracy of decentralized optimal control in the prior art, provides stability and accuracy for reconfigurable robots, and can meet needs of various tasks.

Description

technical field [0001] The invention relates to a distributed nerve optimal control method of a reconfigurable robot system, which belongs to the field of robot control algorithms. Background technique [0002] A reconfigurable robot consists of a power supply unit, a deceleration device, actuators, sensors, and a computing system. These modules can be assembled to predetermined parameters with standard mechanical interfaces to meet the needs of various tasks. Starting from this advantage, reconfigurable robots are often used in complex and dangerous working environments, such as disaster relief, space exploration, high-temperature / low-temperature operations, etc. Therefore, a reconfigurable robot requires an appropriate control system to guarantee the stability of the robot system, while considering the optimal implementation of the combination of control performance and power consumption. [0003] An important property of reconfigurable robots is that robot modules can b...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 董博安天骄秦一靳伟宁周帆王树祥刘克平李元春
Owner CHANGCHUN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com