Title
Online Optimization of Fuzzy Controller for Coke-Oven Combustion Process Based on Dynamic Just-in-Time Learning
Abstract
To guarantee the control performance of a fuzzy control system for the combustion process in a coke oven, the parameters of the fuzzy controller need to be optimized so that the controller can handle large changes in the operating state of the oven. This paper describes an online optimization method for this purpose. In this method, the distance and angle of the trend of the change are used to select data, and just-in-time learning is used to create a dynamic sample base and to build a radial-basis-function neural-network model of the process. A variable-universe fuzzy logic controller controls the process, and an adaptive differential evolution algorithm optimizes the universe parameters. This enables the controller to adapt to changes in the operating state in a timely fashion. Simulation results demonstrate the effectiveness of the method.
Year
DOI
Venue
2015
10.1109/TASE.2015.2461024
Automation Science and Engineering, IEEE Transactions
Keywords
Field
DocType
Optimization,Combustion,Ovens,Heating,Fuzzy logic,Fuzzy control,Coal gas
Data modeling,Control theory,Control theory,Computer science,Fuzzy logic,Control engineering,Coke,Process control,System dynamics,Fuzzy control system,Open-loop controller
Journal
Volume
Issue
ISSN
PP
99
1545-5955
Citations 
PageRank 
References 
4
0.48
5
Authors
3
Name
Order
Citations
PageRank
Lei, Q.163.26
Min Wu23582272.55
Jin-Hua She31841182.27