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

Extreme random tree furnace temperature prediction control method based on longicorn beard search

A predictive control, random tree technology, applied in computer parts, computer-aided design, instruments, etc., can solve the problem of low accuracy of system models, and achieve good prediction effect, ensure reliability, and high precision.

Pending Publication Date: 2021-01-01
JIANGNAN UNIV
View PDF12 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The classic predictive control algorithm generally establishes a system model by obtaining the system's step or impulse response parameters, and obtains an approximately linear model. However, for systems with nonlinear and more interference, there is a problem of low accuracy of the system 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
  • Extreme random tree furnace temperature prediction control method based on longicorn beard search
  • Extreme random tree furnace temperature prediction control method based on longicorn beard search
  • Extreme random tree furnace temperature prediction control method based on longicorn beard search

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0082] Using an extremely random tree furnace temperature prediction control method based on longhorn beetle search proposed by the present invention, randomly derived 5 days of field data from the database, and found that the range of natural gas flow and furnace temperature on August 10, 2018 was very large Large, covering almost all possible working conditions on site. A total of 32,600 sets of data were collected that day, and the sampling period was T=0.1s. Randomly select 3000 groups from these 32600 groups of data, and select 2700 groups by cross-validation method as the training set of the extreme random tree algorithm 1 ={(A 1 ,y 1 ),(A 2 ,y 2 )…(A 2700 ,y 2700 )}, A iis a 1×5-dimensional row vector, a set of input quantities for modeling samples, y i is A i The actual output of the corresponding modeling samples, i=1,2,...,2700; the remaining 300 groups are used as the test set Ω 2 ={(B 1 ,y 1 ),(B 2 ,y 2 )…(B 300 ,y 300 )}, B i is a 1×5-dimensional ...

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 an extreme random tree furnace temperature prediction control method based on longicorn beard search, and belongs to the field of furnace temperature prediction and control inthe industrial combustion process. By establishing the regression relation between the key variables influencing the temperature and the temperature of the combustion chamber, the predicted value of the furnace temperature in the combustion chamber is obtained in real time, and the prediction precision of the furnace temperature reaches + / -1.5 DEG C. In consideration of low control precision of anoriginal system, a longicorn beard search algorithm is designed, a secondary performance index function commonly used in predictive control is selected as a fitness function of longicorn, and an optimal control quantity is searched through an olfaction search mechanism of the algorithm, so that the control effect of the whole system is better.

Description

technical field [0001] The invention belongs to the field of furnace temperature prediction and control in the industrial combustion process, in particular to an extreme random tree prediction control method based on longhorn beetle search. Background technique [0002] With the increasingly stringent control of environmental pollution, the effective treatment of low-concentration volatile organic compounds (Volatile Organic Compounds, VOCs) from petrochemical, papermaking, paint, printing and dyeing and other industrial production has received great attention in China. At this stage, the most commonly used equipment for VOCs treatment in my country is regenerative thermal oxidizer (Regenerative Thermal Oxidizer, RTO). The traditional RTO adopts simple PID control for the temperature in the combustion chamber, while the oxidation furnace is essentially a large inertia, large lag and multivariable nonlinear system. When the working conditions in the combustion chamber change,...

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): G06F30/27G06K9/62G06F119/08
CPCG06F30/27G06F2119/08G06F18/24323
Inventor 张相胜徐晓燕李兆鹏
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