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In this article, the diagnosability problem is investigated for open-loop and closed-loop stochastic systems under sensor and actuator faults. A novel quantitative fault diagnosability analysis method is developed to characterize the detectability and isolability for a given system without any predetermined fault diagnosis algorithm. By exploiting the Bhattacharyya distance, some novel indices are proposed to evaluate the difficulty degree of fault detectability and isolability. Necessary and sufficient conditions are established for the diagnosability of both open- and closed-loop stochastic systems undergoing sensor and actuator faults. In addition, the relationship between the fault detectability of open-loop systems and that of closed-loop ones is discussed. [ABSTRACT FROM AUTHOR]

In this article, a new event-triggered Hi/H∞ optimization fault detection (FD) scheme is proposed for linear discrete time systems. A linear discrete time system with varying sampling periods is first presented to describe the dynamics of an event-triggered system. Based on this, an observer-based fault detection filter (FDF) is constructed as an event-triggered residual generator so that the generated residual signal is completely decoupled from the event-triggered transmission error. The design of event-triggered FDF is formulated as a multiobjective optimization problem denoted by Hi/H∞ and an optimal solution can be obtained by recursive calculation of Riccati equations. In addition, an event-triggered residual evaluation strategy is also presented. Comparing with the existing event-triggered FD schemes, the major contribution of this article is to decouple the residual signals from the event-triggered transmission errors completely and, consequently, the FD performance can be improved significantly. Moreover, an optimal tradeoff between the robustness of residual to unknown input and the sensitivity of residual to fault is achieved in the sense of Hi/H∞ optimization, while the design of FDF and event generator can be carried out independently. To demonstrate the effectiveness of the proposed method, a vehicle lateral dynamic system is used as a simulation example. [ABSTRACT FROM AUTHOR]

In this note, a new scheme of fault detection (FD) is proposed for linear discrete time-varying (LDTV) systems subject to l2-norm bounded unknown inputs. The basic idea is to find an optimal estimation of the l2-norm of the unknown inputs including the unknown initial state variables. This leads to a natural design of the FD system with the l2-norm boundedness of the unknown inputs as a threshold and the l2-norm of the unknown input estimate as the evaluation function. To avoid heavy computational burden, projection technique in Krein space is applied which allows a recursive computation of the evaluation function. It is shown that the achieved FD system satisfies both the worst case and best case sensitivity/robustness ratio criteria and further applications to observer-based FD lead to an alternative design of H\infty/H\infty and/or H-/H\infty fault detection filter. [ABSTRACT FROM PUBLISHER]