ACTIVE FAILURE DETECTION: AUXILIARY SIGNAL DESIGN AND ON-LINE DETECTION R. Nikoukhah ∗ , S. L. Campbell † ∗ INRIA, Rocquencourt BP 105, 78153 Le Chesnay Cedex, France. fax: +(33) 1-39-63-57-86 e-mail: ramine.nikoukhah@inria.fr † Department of Mathematics, North Carolina State University, Raleigh, NC 27695-8205, USA. fax: 1-919-515-3798 e-mail: slc@math.ncsu.edu http://www.math.ncsu.edu/˜slc Keywords: Failure detection, Auxiliary Signal, Model Identification. Abstract This paper describes an active approach for model identification and failure detection in the presence of quadratically bounded uncertainty. After developing the underlying geometry, two particular examples of this approach involving static and continuous models are described. Several examples are given. 1 Introduction There are two general approaches to failure detec- tion and isolation. One is a passive approach where a detector monitors input and outputs of the system and decides whether, and if possible what kind of, a failure has occurred. A passive approach is used for continuous monitoring. The detector has no way of acting upon the system. In contrast, in an active approach the system is acted upon on a periodic basis or at critical times using a test signal (auxiliary signal) to exhibit abnormal be- haviors. The decision of whether or not the system has failed should be made by the end of the test pe- riod. The active approach has the advantages that it can sometimes detect failures that are not detectable during the normal operation of the system. This is especially important for evaluating subsystem status before the subsystem’s performance becomes cru- cial. An example would be evaluating the brakes Figure 1: General system structure. while moving but before a truck has to stop. An ac- tive approach also often permits quicker detection of a failure. Of course, it is usually important that the test signal be small in some sense in order to not in- terfere with normal operation. In [2, 3, 4, 5] we have begun the investigation of a multi-model active approach for model identifica- tion and failure detection. These earlier papers have focused on the theory and computation for various special cases. As this work has progressed a general framework encompassing all of these cases and sev- eral additional ones has begun to become evident. This paper will discuss this general framework for the first time. 2 Geometry of the approach The structure of the active failure detection method considered here is described in Figure 1. The system is acted on by both a control input u and the auxil- iary signal v. The system is subject to noise ν and there is an output y. The information available for