Sensor Fault Detection in A Satellite Launcher Using Adaptive Neuro-fuzzy Observer

Abstract

Fault detection is performed by estimating the states and comparing them with measured values. A fault is signaled when the difference between the estimated and measured values crosses a threshold value, This paper presents the design of adaptive neuro-fuzzy observer based sensor fault detection and fault tolerant control under sensor failure conditions for a satellite launcher. In this Adaptive Neuro-Fuzzy Inference System (ANFIS), optimal shape and parameters for the membership functions and effective rule base for the fuzzy system are fixed by a neural network. Three such adaptive neuro-fuzzy inference systems act as reduced order observers that estimate the system states. Decision functions are built from estimation errors to detect the fault. If any failure is identified, the control law is modified accordingly using the estimated value replacing the failed sensor output to implement the fault tolerant control. In this work, such fault detector is designed and simulated. The individual failures of three sensors in the satellite launcher are considered and the results are discussed. The results show that the system is able to detect any sensor failure situations perfectly.