Design of Fuzzy Terminal Iterative Learning Control based on internal model control

Author

Beauchemin-Turcotte, Mathieu ; Gauthier, Guy ; Sabourin, R.

Author_Institution

Dept. of Automated Manuf. Eng., Ecole de Technol. Super., Montreal, QC, Canada

fYear

2014

fDate

16-19 June 2014

Firstpage

463

Lastpage

468

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.

Keywords

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; Fuzzy sets; Interpolation; MIMO; Mathematical model; Process control; Thermoforming; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation (MED), 2014 22nd Mediterranean Conference of

Conference_Location

Palermo

Print_ISBN

978-1-4799-5900-6

Type

conf

DOI

10.1109/MED.2014.6961416

Filename

6961416