Aeroengine thrust estimation is an important problem for direct thrust control since it is unmeasurable. Many methods and algorithms have been proposed to solve this problem. Unfortunately, almost all these methods can only estimate aeroengine thrust when the engine is in steady state. Hence, this study proposes an algorithm based on long short-term memory networks and gradient boosting for aeroengine thrust estimation in transition state. The newly proposed algorithm can estimate thrust of an aeroengine when its working state is changed from one steady state to another. The experimental results demonstrated that the proposed algorithm can be well applied to estimate aeroengine thrust in transition state and the estimated precision can meet the requirements of thrust estimation.

航空发动机推力估算是直接推力控制的重要问题，因为它无法测量。已经提出了许多方法和算法来解决这个问题。不幸的是，几乎所有这些方法只能在发动机处于稳定状态时估算航空发动机推力。因此，本研究提出了一种基于长短期记忆网络和梯度提升的过渡状态航空发动机推力估计算法。当航空发动机的工作状态从一种稳态变为另一种稳态时，新提出的算法可以估算其推力。实验结果表明，该算法可以很好地应用于过渡状态下航空发动机推力的估算，其精度可以满足推力估算的要求。