An Alternative Parity Space-Based Fault Diagnosability Analysis Approach for Linear Discrete Time Systems

This paper deals with the problem of parity space-based fault diagnosability analysis for linear discrete time systems. The main contribution lies in the design of the fault diagnosability evaluation indexes by combining the distance difference information with the direction difference information between the residuals in different cases. Under the assumption that the unknown inputs are random white noises, the residual generation is achieved by the parity space-based fault diagnosis approach. Based on this, the problem of fault diagnosability analysis is formulated as a bank of evaluation problems of the difference information between two residuals in fault-free case or in different faulty cases. Then, the fault diagnosability evaluation indexes are proposed based on the integrated design of the distance similarity function and the direction similarity function between different residuals, and the improved fault isolation conditions are constructed to provide an auxiliary index for fault diagnosability analysis. A simulation is carried out on a fixed-wing unmanned aerial vehicle flight control system, and the results demonstrate that the proposed method can achieve fault diagnosability analysis accurately for the linear discrete time systems.