@inproceedings{ac0401e0ab444fa490b92e02f669afa5,
title = "A Non-iterative Turboshaft Engine Model with Its Neural Network Control Algorithm",
abstract = "In this paper, the volumetric method model based on volume dynamics is used to model the turboshaft engine instead of the general iterative model, which solves the problem of poor real-time and slow speed of the iterative model. The PID control strategy based on BP neural network is used to make the three parameters of PID control adaptive and self-learning. Simulation tests were performed under transition state operating conditions and compared with normal PID control. The results show that the BP neural network-based PID control provides considerable performance optimization to meet the control requirements of the engine and outperforms the conventional PID control algorithm in terms of response time and response accuracy.",
keywords = "BP neural network, PID control, Turboshaft engine, Volumetric method",
author = "Tianhao Jia and Yue Ma",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 19th Chinese Intelligent Systems Conference, CISC 2023 ; Conference date: 14-10-2023 Through 15-10-2023",
year = "2023",
doi = "10.1007/978-981-99-6886-2_39",
language = "English",
isbn = "9789819968855",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "451--459",
editor = "Yingmin Jia and Weicun Zhang and Yongling Fu and Jiqiang Wang",
booktitle = "Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III",
address = "Germany",
}