Share Email Print
cover

Proceedings Paper

Microturbine control based on fuzzy neural network
Author(s): Shijie Yan; Chunyuan Bian; Zhiqiang Wang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

As microturbine generator (MTG) is a clean, efficient, low cost and reliable energy supply system. From outside characteristics of MTG, it is multi-variable, time-varying and coupling system, so it is difficult to be identified on-line and conventional control law adopted before cannot achieve desirable result. A novel fuzzy-neural networks (FNN) control algorithm was proposed in combining with the conventional PID control. In the paper, IF-THEN rules for tuning were applied by a first-order Sugeno fuzzy model with seven fuzzy rules and the membership function was given as the continuous GAUSSIAN function. Some sample data were utilized to train FNN. Through adjusting shape of membership function and weight continually, objective of auto-tuning fuzzy-rules can be achieved. The FNN algorithm had been applied to "100kW Microturbine control and power converter system". The results of simulation and experiment are shown that the algorithm can work very well.

Paper Details

Date Published: 6 November 2006
PDF: 7 pages
Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63574P (6 November 2006); doi: 10.1117/12.717468
Show Author Affiliations
Shijie Yan, Northeastern Univ. (China)
Chunyuan Bian, Northeastern Univ. (China)
Zhiqiang Wang, Beihang Univ. (China)


Published in SPIE Proceedings Vol. 6357:
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
Jiancheng Fang; Zhongyu Wang, Editor(s)

© SPIE. Terms of Use
Back to Top