A thrust degradation mitigation neural network control method of aircraft engine was proposed based on variable incremental linear programming (LP) optimization

due to performance deterioration of the gas path components. This method alleviated the engine thrust degeneration through control of high-pressure rotor speed and the engine pressure ratio by the inner loop

and correction of the engine command signal by the outer loop. The inner loop nonlinear autoregressive moving average (NARMA-L2) speed controller was obtained by neural network

and the outer command correction loop used the variable incremental LP optimization method to adjust the engine command signal. Simulations on a low-bypass-ratio-turbofan engine were performed. Results showed that under the 4 sets of simulation conditions

the designed control method can mitigate the thrust at least 46.5%

ensuring that the engine with performance deterioration was not overrun. The effectiveness of the method has been verified.