Application of Neural Network Technology and High-performance Computing for Identification and Real-time Hardware-in-the-loop Simulation of Gas Turbine Engines
Abstract The engineering method for the recurrent neural network construction and identification of a mathematical model of gas turbine engines on a real data is proposed, describing the learning algorithm and the network structure. The complete process of modeling and experimental investigation – from designing of a gas turbines model in form of neural networks to its testing and debugging on the test-bed – are presented. The method was approved on a hardware-in-the-loop test-bed with a FADEC closed loop control for the start-up, ground and flight modes.
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Application of Neural Network Technology and High-performance Computing for Identification and Real-time Hardware-in-the-loop Simulation of Gas Turbine Engines
Semantic Scholar · Engineering · 2017
Abstract
Abstract The engineering method for the recurrent neural network construction and identification of a mathematical model of gas turbine engines on a real data is proposed, describing the learning algorithm and the network structure. The complete process of modeling and experimental investigation – from designing of a gas turbines model in form of neural networks to its testing and debugging on the test-bed – are presented. The method was approved on a hardware-in-the-loop test-bed with a FADEC closed loop control for the start-up, ground and flight modes.