Microturbine control based on fuzzy neural network

Shijie Yan; Chunyuan Bian; Zhiqiang Wang

doi:10.1117/12.717468

6 November 2006 Microturbine control based on fuzzy neural network

Shijie Yan, Chunyuan Bian, Zhiqiang Wang

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 63574P (2006) https://doi.org/10.1117/12.717468
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

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.

Citation Download Citation

Shijie Yan, Chunyuan Bian, and Zhiqiang Wang "Microturbine control based on fuzzy neural network", 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); https://doi.org/10.1117/12.717468

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