Optimal control method for reaction regeneration system based on qpso-dmpc

A QPSO-DMPC, reaction regeneration technology, applied in data processing applications, forecasting, instruments, etc., can solve the problems of heavy hardware burden and low control precision, and achieve the goal of reducing hardware burden, high randomness, and optimal operating variable parameters Effect

Active Publication Date: 2020-08-25
CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of the above problems, the purpose of the present invention is to provide a QPSO-DMPC-based reaction regeneration system optimization control method to solve the problems of low control accuracy and large hardware burden of the existing nonlinear reaction regeneration system

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
  • Optimal control method for reaction regeneration system based on qpso-dmpc
  • Optimal control method for reaction regeneration system based on qpso-dmpc
  • Optimal control method for reaction regeneration system based on qpso-dmpc

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0015] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that these embodiments may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing one or more embodiments.

[0016] Glossary

[0017] DMPC: The Double-layerd Model Predictive Control, double-layer model predictive control.

[0018] QPSO: Quantum-behaved Particle Swarm Optimization algorithm, quantum particle swarm optimization algorithm.

[0019] figure 1 The flow chart of the QPSO-DMPC-based reaction regeneration system optimization control method according to the present invention is shown.

[0020] Such as figure 1 As shown, the QPSO-DMPC-based reaction regeneration system optimization control method provided by the invention comprises the following steps: ...

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 reaction regeneration system optimization control method based on QPSO-DMPC, the method comprises following steps; S1, a transfer function model of a reaction regeneration system is converted as a step response model; S2, a DMPC model is established and comprises an open loop prediction module, a steady state target calculation module and a dynamic matrix control module; S3, strong randomness of particles in a search space in a QPSO algorithm is utilized, in a condition of no relaxing constraint conditions, an economic optimization function is solved in a larger area than before; S4, an output set value of the reaction regeneration system is obtained through the result obtained by solving the economic optimization function according to the QPSO algorithm, a bias between the output set value and actual output serves as a target error function, the QPSO algorithm is utilized to solve the target error function, and an optimal variation of an operating variable is obtained. According to the invention, the RRS hardware burden can be reduced, better operating variable parameters can be obtained, and optimization control is performed on RRS based on ensuring the economic benefits.

Description

technical field [0001] The invention belongs to the technical field of petrochemical industry, and relates to a QPSO-DMPC-based optimization control method for a reaction regeneration system. Background technique [0002] The petrochemical industry occupies a pivotal position in my country's national economy and bears the burden of providing various energy sources for our country. Conventional catalytic cracking unit consists of three parts, including reaction regeneration system, fractionation system and absorption stabilization system. As the core part of catalytic cracking, the reaction regeneration system (Reaction regeneration system, RRS) processes crude oil to produce various light oil products. However, the existing reaction regeneration system is a nonlinear reaction regeneration system, which has the problems of low control precision and heavy hardware burden. Contents of the invention [0003] In view of the above problems, the purpose of the present invention...

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): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/067G06Q50/06
Inventor 陈雪梅吴凌白竣仁周伟陈实易军
Owner CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap