IMC based automatic tuning method of PID controllers using neural networks

Author

Chibani, R. ; Chtourou, M.

Author_Institution

Dept. of Electr. Eng., Nat. Sch. of Eng. of Sfax, Sfax

fYear

2009

fDate

23-26 March 2009

Firstpage

1

Lastpage

5

Abstract

In this paper, a new approach for neural PID tuning is presented based on the use of a neural network and the internal model control (IMC) principle. The neural network is used to adjust on line the PID controller after an off line training step. The developed approach is based on the use of a neural supervisor having as inputs the control signal, its correspondent output and the filter time constant and the PID parameters as outputs. The design of the supervisor is based on the procedures of linearization and IMC principle. We briefly outline the content of the tuning course and finish the paper with illustrative example where good performances have been obtained.

Keywords

control system synthesis; linearisation techniques; neurocontrollers; robust control; three-term control; IMC based automatic tuning; IMC principle; PID controller; PID parameter; control signal; filter time constant; internal model control; linearization; neural PID tuning; neural network; neural supervisor; robust control; Automatic control; Design optimization; Filtering; Filters; Lattices; Neural networks; Reflection; Robust control; Robustness; Three-term control; IMC control; Neural Networks; PID controller; Supervision;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Devices, 2009. SSD '09. 6th International Multi-Conference on

Conference_Location

Djerba

Print_ISBN

978-1-4244-4345-1

Electronic_ISBN

978-1-4244-4346-8

Type

conf

DOI

10.1109/SSD.2009.4956702

Filename

4956702