Fault Detection and Isolation of Sensors in Dynamic Systems with Modelling Uncertainties

Abstract

This paper deals with the problem of modelling the influence of unknown time-varing parameters on linear dynamic system response. These parameters are introduced through the appropriate parts of the system matrix description in the state-space domain. The author shows that their influence can be efficiently estimated by dynamic programming, thus resulting in the so-called permissible interval of the system output. This interval defines the worst case of the uncertain parameters influence and defines the upper and lower bounds of the system response. The approach is further applied to a full-order classical observer-based scheme for fault detection and isolation of sensors, greatly enhancing its robustness. Suitable choice of the observer gain matrix is shown to significantly improve fault-detection and isolation capability. The theoretical results are illustrated by simulation of some faults modes on an aircraft example. These results verify that the proposed fault detection observer scheme can be efficiently used in dynamic systems with modelling uncertainties (errors).

Key Words:

• Dynamic systems
• sensors
• fault detection and isolation
• robustness
• dynamic programming

Additional information

Notes on contributors

P. Rakic

Predrag Rakic received his B.Sc. in electrical engineering from Belgrade University in 1983 and his M.Sc. in logistics from Belgrade University in 1991. His master's thesis was entitled “An approach to phased mission system reliability modeling.” He is currently working on his Ph.D. thesis: “On using dynamic programming to improve fault detection in dynamic systems with modeling errors.” He is a senior research engineer at the Institute of Nuclear Sciences—Vinca. His interests also include adaptive control, computer simulation, and distributed processing.