Model-Based Improved Advanced Adaptive Performance Recovery Control Method for a Commercial Turbofan Engine
Qian Chen, Hanlin Sheng, Jiacheng Li, Tong Liu
Abstract
In-service commercial aeroengine controls its thrust by controlling parameters, such as speed/pressure ratio (Nf/EPR), characterized as measurable and indirectly related to the thrust. However, the mapping relationship between the Nf/EPR and the thrust would have unknown and nonlinear changes as the engine performance degrades, naturally making it difficult to obtain the desired thrust by primarily designing Nf/EPR control and resulting in task degradation. Therefore, this article proposes an improved double closed-loop self-adaptive performance recovery control method to allow the engine to maintain almost consistent performance in the whole life cycle. First, the inner control loop of speed is designed based on the model predictive control (MPC) algorithm to obtain the optimal fuel output through receding horizon optimization to improve the control performance. Second, the speed command from the inner control loop of the degraded engine is compensated by adding an outer control loop of thrust to maintain the desired thrust. In this control method, an improved high-precision parameter estimation method is presented to estimate unmeasurable engine performance parameters. A steady-state identification algorithm therein is designed to judge the engine state to deal with the problem that the estimator might diverge due to the engine's strongly nonlinear performance changes under the circumstances of high dynamic operation. Finally, the simulation results show that, compared with the traditional method, the proposed method achieves the estimator's stable work, improves the control performance by 25.8%, and maintains the desired thrust in case of engine degradation.