Application of Neural Network Technology and High-performance Computing for Identification and Real-time Hardware-in-the-loop Simulation of Gas Turbine Engines

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.