Fault diagnosis and estimation for near-space hypersonic vehicle with sensor faults

Abstract

This paper addresses a practical issue in fault diagnosis and estimation for a near-space hypersonic vehicle (NSHV) with sensor faults. First, the Takagi–Sugeno (T–S) fuzzy model is established to represent the NSHV non-linear dynamics, and sliding mode observers (SMO) are designed to generate a bank of residuals. Then, a novel sensor fault model is proposed, which contains time-varying bias faults and time-varying gain faults. Further, based on the Lyapunov stability theory, novel fault diagnostic algorithms are given to estimate the sensor fault, which removes the two classical assumptions in existing works that the time derivative of the output errors should be known and that the system states should be bounded. In addition, a sufficient condition for the existence of SMO is derived in the sense of the Lyapunov stability theory, which can be easily solved by Matlab^® LMI toolbox. Finally, simulation results are presented to demonstrate the efficiency of the proposed approach.