Conference Paper

Virtual sensor for fault detection and isolation in flight control systems - fuzzy modeling approach

Control Eng. Lab., Delft Univ. of Technol.
DOI: 10.1109/CDC.2000.914204 Conference: Decision and Control, 2000. Proceedings of the 39th IEEE Conference on, Volume: 3
Source: IEEE Xplore

ABSTRACT A virtual sensor for normal acceleration has been developed and
implemented in the flight control system of a small commercial aircraft.
The inputs of the virtual sensor are the consolidated outputs of
dissimilar sensor signals. The virtual sensor is a fuzzy model of the
Takagi-Sugeno type and it has been identified from simulated data, using
a detailed, realistic Matlab/SimulinkTM model used by the
aircraft manufacturer. This virtual sensor can be applied to identify a
failed sensor in the case that only two real sensors are available and
even to detect a failure of the last available sensor

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a technique that builds a layer of virtual sensors over a sensor network. The virtual sensors are able to infer and provide data for the physical sensors that do not work. The key assumption of our approach is that the physical quantities sensed by the sensors are related. The relations among sensors are unknown, but during a learning phase the layer of virtual sensors infers an approximation of them by means of fuzzy rules. The inferred fuzzy rules capture these relations in a simple way even when the corresponding mathematical models are complex. The set of fuzzy rules inferred for a node can be used to obtain virtual values when the real ones are not available. In order to develop our technique we improved the Tree Routing Protocol in charge to deliver data from the nodes to the base station and used Snlog, a Datalog-like language that supports the implementation of distributed algorithms for Wireless Sensor Network in a declarative way. We developed a system prototype and performed preliminary experiments that prove the validity of our approach.
    Fourteenth International Database Engineering and Applications Symposium (IDEAS 2010), August 16-18, 2010, Montreal, Quebec, Canada; 01/2010
  • [Show abstract] [Hide abstract]
    ABSTRACT: A virtual sensor uses low-cost measurements and mathematical models to estimate a difficult to measure or expensive quantity. Virtual sensors have been sucessfully developed and applied in other fields within the past two decades. This article reviews developments of virtual sensors in other fields and early applications for buildings. It is believed that widespread application of virtual sensors for buildings would enable a level of building optimization and improvement not previously considered to be economical. It is hoped that this article can provide a resource for these future developments and applications.
    HVAC&R RESEARCH 10/2011; 17(5):619-645. · 0.59 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Attitude estimation using Global Positioning System/Inertial Navigation System (GPS/INS) was used as an example application to study three different methods of fusing redundant multi-sensor data used in the prediction stage of a nonlinear recursive filter. Experimental flight data were collected with an Unmanned Aerial Vehicle (UAV) containing GPS position and velocity calculations and four redundant Inertial Measurement Unit (IMU) sensors. Additionally, the aircraft roll and pitch angles were measured directly with a high-quality mechanical vertical gyroscope to be used as a 'truth' reference for evaluating attitude estimation performance. A simple formulation of GPS/INS sensor fusion using an Extended Kalman Filter (EKF) was used to calculate the results for this study. Each of the three presented fusion methods was shown to be effective in reducing the roll and pitch errors as compared to corresponding results using single IMU GPS/INS sensor fusion. Additionally, the fusion methods were shown to be effective in estimating roll and pitch angles without the aid of GPS (dead reckoning).
    AIAA Guidance Navigation and Control Conference, Minneapolis, MN; 01/2012