Practical Fixed-Time Active Surge Control of Aero-Engines.

Area of Science:

• Aerospace Engineering
• Control Systems

Background:

• Active surge control enhances aero-engine performance but faces challenges with model uncertainty and long surge fault durations.
• Conventional methods struggle to adapt to changing engine dynamics and ensure rapid fault recovery.

Purpose of the Study:

• To propose a novel fixed-time active surge control scheme for aero-engines.
• To improve adaptability to model changes and extend engine service life.
• To address limitations of conventional methods in handling model uncertainty and surge faults.

Main Methods:

• Utilized a radial basis function (RBF) neural network to approximate complex aero-engine dynamics under model uncertainty.
• Developed an adaptive law to optimize the RBF neural network's weight vectors.
• Designed a fixed-time controller to stabilize compressor dynamics by adjusting intake airflow, ensuring rapid fault convergence.

Main Results:

• The proposed scheme effectively approximates system dynamics and adapts to model changes.
• The fixed-time controller ensures rapid stabilization of compressor dynamics, significantly reducing surge fault duration.
• Simulations on a turbofan aero-engine demonstrate the method's superior performance.

Conclusions:

• The novel fixed-time active surge control scheme offers superior performance in expanding stable working ranges and reducing performance loss.
• The method enhances aero-engine adaptability to model variations and extends operational lifespan.
• This approach provides a robust solution for managing surge instability in aero-engines.