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

A system state reverse estimation method of finite estimation interval is introduced

A technology for estimating intervals and system states, applied in complex mathematical operations, measuring devices, instruments, etc., can solve problems such as difficult application of forward estimation

Inactive Publication Date: 2020-09-08
JIANGNAN UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For such scenarios, due to the limitations of its own calculation structure, forward estimation is difficult to apply

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
  • A system state reverse estimation method of finite estimation interval is introduced
  • A system state reverse estimation method of finite estimation interval is introduced
  • A system state reverse estimation method of finite estimation interval is introduced

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0056] The embodiment of the present invention discloses a system state reverse estimation method that introduces a limited estimation interval, refer to figure 1 As shown, the specific steps of the reverse estimation method include,

[0057] In the first step, a linear Gaussian state-space model is constructed for the control loop including the controller:

[0058]

[0059] Among them, k is the time series; x k is the system state variable; y k is the noise-containing observation signal; u k-1 is the controller output; w k-1 is process white noise, and w k-1 ~N(0,Q k ) obey Gaussian distribution; Q k is the known process noise variance, v k is to measure white noise, and v k ~N(0,R k ) obey Gaussian distribution; R k is the observation noise variance; A is the dynamic matrix of the system state; E is the system actuator matrix; C is the observation dynamic matrix; D is the process noise dynamic matrix.

[0060] Due to the relatively large dimension of the state ...

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 system state reverse estimation method for introducing a finite estimation interval. The method comprises the steps: (1) introducing the finite estimation interval [m, n], m= n-N + 1, m and n are two different moments, and N is the step length of the estimation interval; (2) calculating a state estimation value and a variance Pn of the system at the moment n based on a forward recursion Kalman filtering algorithm; and (3) calculating a state estimation value and a variance Pm of the system at the moment m based on a reverse recursion Kalman filtering algorithm by taking the initial state and Pn as an initial variance, and abandoning other state estimation values and variances in the estimation interval [m, n] to complete estimation of the system state. The reverse estimation method can be used for initializing a forward estimation algorithm, and on the other hand, the historical state of the system can be reconstructed under the condition that the current state estimation value is known.

Description

technical field [0001] The invention relates to a state estimation method, in particular to a system state reverse estimation method introducing a limited estimation interval. Background technique [0002] State estimation is to process a series of noise-containing measurement data to obtain the estimated value of the measurand or its linear combination hidden in it. Since most of the control and monitoring mechanisms in modern industry are built on the assumption that the system state is accurate and observable, how to accurately obtain the system state from the actual observation signals subjected to various random disturbances is extremely important. It can be said that the acquisition of system status affects the safety of industrial processes, the economics of production, decision-making in uncertain environments, and the effective implementation of monitoring or control methods. At present, the design ideas of state estimation algorithms for state-space models have be...

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): G06F17/16G01D21/00
CPCG01D21/00G06F17/16
Inventor 赵顺毅赵珂刘飞
Owner JIANGNAN UNIV
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