An expected-mode augmentation-based approach for multiple-fault detection and diagnosis in flight control systems

Abstract

Aircraft fault detection and diagnosis (FDD) is a key technology to ensure flight safety. However, multiple simultaneous fault detection is still a difficult problem. To deal with it, a new FDD approach is proposed in this article, in which the expected-mode augmentation (EMA) approach is applied for the variable-structure interacting multiple model (VSIMM) estimation. The EMA approach is used for online model set adaption. In the EMA–VSIMM FDD approach, the failure model set is composed of a basic fixed model set and an adaptive EMA set. The EMA set is generated based on the basic fixed model set according to their predicted probabilities. Single or multiple simultaneous faults can be detected and diagnosed by applying the EMA set properly. The simulation results show that the EMA–VSIMM method is effective in detecting faults of various types and estimating unknown fault parameters.