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

Fault-tolerant control method based on hidden Markov model

A fault-tolerant control and model technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problems of structural accuracy, low reliability, poor effect of model predictive control, etc.

Pending Publication Date: 2019-04-09
ZHEJIANG WINDEY
View PDF2 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention mainly solves the problems of low structural accuracy and reliability and poor effect of model predictive control in MPC fault-tolerant control in the prior art, and provides a fault-tolerant control method based on hidden Markov model

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
  • Fault-tolerant control method based on hidden Markov model
  • Fault-tolerant control method based on hidden Markov model
  • Fault-tolerant control method based on hidden Markov model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0063] In this embodiment, a fault-tolerant control method based on a hidden Markov model comprises the following steps:

[0064] S1. Offline modeling, collecting training sample sets, using the offline data collected in the industrial process as the observation sequence of the hidden Markov model, and training the hidden Markov model; the specific process includes:

[0065] S11. Use a stochastic nonlinear system to describe the industrial process, and the stochastic nonlinear system is expressed by the following formula:

[0066]

[0067] Where t is the time index, and the superscript [i] represents the working condition index, Indicates the state of working condition i, n x is the number of state variables, Indicates control input, n u is the number of input variables, Indicates time-invariant model parameters, n θ is the number of model parameters, Indicates that with known finite covariance ∑ ω The zero-mean process noise of f [i] : Represents the model eq...

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 invention discloses a fault-tolerant control method based on a hidden Markov model. On-line fault recognition is carried out by utilizing the strong dynamic process time sequence modeling capability and the time sequence mode classification capability of the hidden Markov model, and the diversity factor between PDFs (Probability Density Function) in a predictable state is improved through introduction of Hellinger Distance, so that the accuracy and reliability of fault recognition are improved. According to the method, higher reliability is achieved for ensuring normal operation of an industrial process under a condition that a fault occurs in a strong dynamic industrial process.

Description

technical field [0001] The invention relates to the technical field of industrial process control and diagnosis, in particular to a fault-tolerant control method based on a hidden Markov model. Background technique [0002] As industrial systems become more complex, it becomes increasingly important to ensure safe, reliable, and high-performance operation in the event of system failure. Fault tolerant control methods allow improved fault detectability and isolation in system output through auxiliary input design. [0003] In recent years, Model Predictive Control (MPC) has attracted great attention in the field of industrial control because of its explicit handling of input and output constraints. MPC is a model-based control method, and its control effect depends on whether the prediction model matches the actual object. The MPC algorithm has been proved to have good robust performance. Within a certain degree of model mismatch, good dynamic and static effects can be achi...

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 王琳孙勇傅凌焜陈棋
Owner ZHEJIANG WINDEY
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