Intelligent Fault-Tolerant Control System Design and Semi-Physical Simulation Validation of Aero-Engine

• Published in: IEEE access 2020, Vol.8, p.217204-217212
• Main Authors: Liu, Yuan, Chen, Qian, Liu, Shengyi, Sheng, Hanlin
• Format: Article
• Language: English
• Subjects: Aero-engine; Aerospace engines; Artificial neural networks; Control methods; Control systems; Control systems design; Engines; Fault diagnosis; Fault tolerance; Fault tolerant systems; fault-tolerant control; Machine learning; online sequential extreme learning machine; Physical simulation; Proportional integral derivative; Robust control; semi-physical simulation; Signal reconstruction; Simulation; Sliding mode control; Training; Turbofan engines
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3030157

In order to improve the reliability and real-time of the control system of aero-engine, an intelligent fault-tolerant control system based on the online sequential extreme learning machine (OS-ELM) is proposed against the sensor faults. This system can realize the online fault diagnosis and signal reconstruction without a system model. And while considering the traditional PID control robustness and poor anti-interference ability and other shortcomings, an improved global fast non-singular terminal sliding mode control method is used to obtain better control effects, effectively solve the uncertainty problem in aero-engine, and give full play to aero-engine performance. To verify the feasibility and effectiveness of this system based on the above method, a turbofan engine is taken as the research object and semi-physical simulation experiments on fault-tolerant control are conducted on a semi-physical simulation test platform. Results show that the controller of this system can safely and reliably control the aero-engine without losing its control performance under the circumstance that there are faults in engine sensors. The purpose of fault-tolerant control is reached.