Title
Neural network adaptive autotuner
Abstract
It is critical that modern control theory techniques be integrated into assignments which involve the application of basic concepts in engineering technology to prepare students for the next millennium. The adaptive neural network discussed in this paper can be viewed as an appropriate use of these modern techniques in engineering technology curriculum. Adaptive tuning of PID controller gains in case of plant parameter variations is of great importance. There are many approaches available for PID autotuning. In this paper the PID controller gains are adaptively changed using a neural network approach. The neural network tuner is incorporated in the control system to adapt the PID gains to changing system parameters. The neural network architecture employed is a multilayer perceptron. A computer simulation is conducted to show the tracking behavior of the controller in the case of plant parameter variations and set point changes.
Publication Date
12-1-1998
Publication Title
ASEE Annual Conference Proceedings
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0032302531 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0032302531
STARS Citation
Rahrooh, Alireza and Motlagh, Bahman, "Neural network adaptive autotuner" (1998). Scopus Export 1990s. 3675.
https://stars.library.ucf.edu/scopus1990/3675