Paper Info
Title
Design of Fuzzy Terminal Iterative Learning Control based on internal model control
Abstract
This paper presents an innovative approach to the design of a cycle to cycle control algorithm: Fuzzy Terminal Iterative Learning Control (f-TILC). This is the first fuzzy Terminal Iterative Learning Control (TILC) ever proposed up to now. This fuzzy controller is built from a fuzzy model of the process, based on the 1st order Takagi Sugeno Kwan Fuzzy Inference System. The rule consequents are expressed as matricial equations, and obtained from experimental results and kriging interpolation. Simulation results show the effectiveness of our fuzzy TILC, especially in terms of providing a good initial guess as to the inputs to apply to the control process. This control approach can help to reduce the wastage of products in thermoforming processes.
Year
DOI
Venue
2014
10.1109/MED.2014.6961416
Control and Automation
Keywords
DocType
ISSN
adaptive control,control system synthesis,fuzzy control,iterative methods,learning systems,1st order Takagi Sugeno Kwan fuzzy inference system,cycle to cycle control algorithm design,f-TILC,fuzzy terminal iterative learning control,internal model control,kriging interpolation,matricial equations,products wastage reduction,thermoforming processes
Conference
2325-369X
Citations 
PageRank 
References 
0
0.34
4
Authors
3
Name
Order
Citations
PageRank
Beauchemin-Turcotte, M.100.34
Guy Gauthier2163.34
Robert Sabourin390861.89