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

Yuan Liu,Shengyi Liu,Hanlin Sheng,Qian Chen

doi:10.1109/access.2020.3030157

Abstract

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.

Highlights

With the continuous development of the modern aero-engine control technology, the continuous improvement of performance has led to the continuous upgrade of system complexity, and its requirements of safety and reliability have become more stringent[1]
Wallhagen and Arpasi [7] performed fault diagnosis by comparing the response difference of the engine output between step input and normal control, and on this basis, the fault sensor signal is reconstructed by the resolution margin to realize the fault tolerance of the rotational speed closed-loop control loop; Napolitano and Silvestri [8] proposed a sensor fault diagnosis and fault-tolerant control method based on online BP(Back Propagation) neural network
This paper proposed a design of an intelligent fault-tolerant control system based on online sequential extreme learning machine (OS-ELM) from the perspective of engineering application and semi-physical simulations for fault-tolerant control against failures in the high-pressure rotor sensor were conducted

Summary

INTRODUCTION

With the continuous development of the modern aero-engine control technology, the continuous improvement of performance has led to the continuous upgrade of system complexity, and its requirements of safety and reliability have become more stringent[1]. Later Zhou et al [25] proposed a sensor fault diagnosis algorithm based on the selective updating regularized online sequential extreme learning machine (SROS-ELM) algorithm, and realized the semi-physical simulation test, but did not design the fault-tolerant control system, and in terms of real-time performance, the SROS-ELM algorithm slightly worse than the OS-ELM algorithm [26]. This paper will start from the actual engineering application value, consider the algorithm complexity and real-time requirements, and design an aero-engine intelligent fault-tolerant control system based on the OS-ELM algorithm, 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(SMC) method [30]–[32] is used to obtain better control effects, effectively solve the uncertainty problem in aero-engine, and give full play to aero-engine performance.

AERO-ENGINE FAULT DIAGNOSIS MODULE DESIGN BASED ON OS-ELM

THE DESIGN OF AEROENGINE FAULT TOLERANT CONTROL SYSTEM

CONCLUSION