Intelligent algorithm for solution of nonlinear mathematical model for aeroengine

被引：0
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作者：
Engineering Inst., Air Force Engineering Univ., Xi'an 710038, China [1 ]
机构：
来源：
Tuijin Jishu | 2008年 / 5卷 / 614-616期
关键词：
Genetic algorithms - Newton-Raphson method - Flight simulators - Aircraft engines - Flight envelopes;
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摘要：
Current solutions are not always convergent while genetic algorithm is inefficient. Because of this, BP neural networks was used to approach the inverse function of balance equations, and the approximate solution was used as the initial value of Newton-Raphson algorithm, thus an intelligent algorithm is proposed. Simulation results show that this algorithm can make nonlinear mathematical model for aeroengine convergent in the entire flight envelope, and also has higher efficiency compared with genetic algorithm.
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