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Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

  • Hanlin Sheng EMAIL logo und Tianhong Zhang
Veröffentlicht/Copyright: 18. Januar 2017
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Abstract

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm – gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

Acknowledgments

This work was supported by National Natural Science Foundation of China (No.51176075,No. 51576097), Funding of Jiangsu Innovation Program for Graduate Education (No.CXZZ13_0176).

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Received: 2016-7-21
Accepted: 2016-9-1
Published Online: 2017-1-18
Published in Print: 2017-8-28

© 2017 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 19.1.2026 von https://www.degruyterbrill.com/document/doi/10.1515/tjj-2016-0051/pdf
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