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Abstract

This paper deals with the detection of Oscillatory Failure Cases (OFC) in Electrical Flight Control System (EFCS) of civil airplanes. The proposed approach uses interval analysis to identify a fault model once a fault has occurred in the physical system. The interval estimation method results are guaranteed and computations are performed in finite time. Failures are identified using the fault models which are checked against system input and output measurements.

Abstract

This paper deals with the problem of diagnosing systems that exhibit both continuous and discrete event dynamics. The proposed approach combines techniques from both continuous and discrete event diagnosis fields. On the on hand, an extension of the parity space approach is used to associate signatures to every operational mode of the system. On the other hand, signature switches arising from the transition from one mode to another are abstracted in the form of a set of events that capture the continuous dynamics. These events are merged into the original discrete dynamic model of the system, allowing us to apply the well-known discrete-event-systems diagnoser approach. This is illustrated on an example that shows the diagnosability improvement of the hybrid approach.

Abstract

Many techniques in model-based diagnosis and other research fields find the hitting sets of a group of sets. Existing techniques apply to sets of finite elements only. This paper addresses the computation of the hitting sets of a group of sets whose elements are convex or non-convex, bounded or unbounded continuous regions. We assume the conflict sets are known and we present a novel procedure, the Continuous Hitting Set algorithm (CHS) for transforming conflict sets of continuous elements into minimal hitting sets.

Abstract

In this paper we propose a hybrid system modeling framework aimed at analyzing diagnosability. In this framework, the hybrid system is seen as the composition of an underlying discrete event and an underlying continuous systems. Diagnosability of these two underlying systems are fully analyzed and new results are provided for the underlying continuous system (called the multimode system). Based on these results, a hybrid language that contains natural discrete events and discrete events capturing the continuous dynamics, is defined. On the basis of this language the diagnosability definition of hybrid systems is provided. With respect to this definition, we prove that the diagnosability of the underlying continuous or the discrete event system is only a sufficient condition. Diagnosability of hybrid systems must be decided by coupling both discrete event and continuous informations. Finally, the necessary and sufficient condition of hybrid diagnosability is given.

Abstract

Interval models may be seen as a trade-off between numerical and qualitative models. They have been often referred as semi-qualitative models. The interval algebra is indeed a specific qualitative algebra with advantageous algebraic properties. This paper presents the application of an interval based parameter estimation method, which is used for learning fault models supporting the detection of Oscillatory Failure Cases (OFC) in Electrical Flight Control System (EFCS) of civil airplanes. The interval estimation method results are guaranteed and computations are performed in finite time. Failures are identified using the fault models which are checked against system input and output measurements.