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

Adaptive staggered reinforcement learning method of DT affine nonlinear system based on matching or mismatching uncertainty

An affine nonlinear and uncertain technology, applied in the field of industrial control, can solve problems such as complex nonlinear characteristics

Active Publication Date: 2020-11-03
LIAONING UNIVERSITY OF PETROLEUM AND CHEMICAL TECHNOLOGY
View PDF3 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The fundamental difference between DT systems and continuous-time systems poses a challenge to solve this problem, and the nonlinear characteristics of DT systems will make it more complicated

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
  • Adaptive staggered reinforcement learning method of DT affine nonlinear system based on matching or mismatching uncertainty
  • Adaptive staggered reinforcement learning method of DT affine nonlinear system based on matching or mismatching uncertainty
  • Adaptive staggered reinforcement learning method of DT affine nonlinear system based on matching or mismatching uncertainty

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0075] An adaptive interleaved reinforcement learning method based on matching or mismatching uncertain DT affine nonlinear systems, by selecting an appropriate utility function, the robust control problem is transformed into the optimal control problem of the standard system, and the simplified For the HJB equation, performance evaluation and control strategy update are alternately implemented at each time step, combined with neural network approximation, so as to ensure the uniform ultimate bounded (UUB) stability of the DT affine nonlinear system, allowing all unknown bounded uncertainties realization. The convergence of the proposed interleaved RL method and the UUB stability of uncertain systems are rigorously proved; the specific steps are as follows: (1) Based on the problem of optimal control, the matched and mismatched uncertain DT affine non- Robust Stability Conditions for Linear Systems. (2) Interleaved RL combined with neural network approximation is proposed to ...

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

An adaptive staggered reinforcement learning method of a DT affine nonlinear system based on matching or mismatching uncertainty belongs to the technical field of industrial control, and comprises thefollowing steps: (1) deriving robust stability conditions of the matching and mismatching DT affine nonlinear system based on the problem of optimal control; and (2) searching a consistent final bounded (UUB) stability robust control strategy in combination with an interleaved RL method of neural network approximation. According to the method, the robust controller of the DT affine nonlinear system is solved by establishing a simplified Hamiltonian Jacobian (HJB) equation, and the method is more general in the applicability significance of unknown structure matching uncertainty and non-structure matching uncertainty.

Description

technical field [0001] The invention belongs to the technical field of industrial control, and in particular relates to an adaptive interleaved reinforcement learning method for an uncertain affine nonlinear discrete-time (DT) affine nonlinear system based on matching or mismatching uncertainty. Background technique [0002] Although there have been a lot of research results in the field of robust control, designing robust controllers for nonlinear systems from the perspective of discrete-time sampling is still a problem worth studying. The above results on robust control apply only to continuous-time linear or nonlinear systems. Since discrete-time controllers have the important advantage that they can be directly implemented digitally with modern embedded hardware, the question of how to design robust controllers for systems, especially nonlinear DT systems, directly in discrete time naturally arises. The essential difference between DT systems and continuous-time systems...

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 Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 李金娜肖振飞王佳琦王春彦闫立鹏
Owner LIAONING UNIVERSITY OF PETROLEUM AND CHEMICAL TECHNOLOGY
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