A neural network learning-based global optimization approach for aero-engine transient control schedule-Reference-Cited by-同舟云学术

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A neural network learning-based global optimization approach for aero-engine transient control schedule

Published:2022-01 Issue: Volume:469 Page:180-188
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Xiaobo,Wang Zhanxue,Xiao Bing,Ye Yifan

Funder

National Natural Science Foundation of China

National Major Science and Technology Projects of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference33 articles.

1. H_∞)refined antidisturbance control of switched LPV systems with application to aero-Engine;Yang;IEEE Trans. Ind. Electron.,2019

2. Study on optimal acceleration control of constrained jet engine based on nonlinear programming;Wang;Acta. Aeronaut. Astronaut. Sin.,1992

3. Optimal design of accelerating control law for variable geometry turbofan engine;Ding;J. Propul. Technol.,1999

4. Optimal acceleration control of turbo-fan engine with genetic algorithm;Shi;J. Propul. Technol.,2003

5. Application of SQP to multi-object optimization of turbofan engine acceleration control;He;J. Aerosp. Power.,2001

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