An unknown input Kalman filter based component FDI algorithm and its application in automobiles. (4th January 2008)

• Record Type: Journal Article
• Authors: Mondal, S.; Chakraborty, G.; Bhattacharyya, K.
• Is Part Of: International journal of vehicle autonomous systems. Volume 5:Number 3/4(2007)
• Page Start: 274
• Page End: 287
• Publication Date: 2008-01-04
• Subjects: automotive fault detection -- fault isolation -- unknown input -- Kalman filter -- observability -- residual -- parameter isolation -- road vehicles -- modelling -- automobile industry; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; Motor vehicles -- Electronic equipment -- Periodicals; Robots -- Control systems -- Periodicals; Intelligent transportation systems -- Periodicals; 629.20285
• Languages: English
• ISSNs: 1471-0226

Abstract

An Unknown Input Kalman Filter (UIKF) based Component Fault Detection and Isolation (CFDI) technique for a dynamical system, affected by both plant and measurement noise, is presented. The Fault Detection and Isolation (FDI) algorithm, which consists of two steps, is developed with the assumption that the fault occurs in a single component of the system. In step 1, the detection of the fault and the isolation of the faulty region are achieved. In the next step, the faulty parameter is isolated from the faulty region. The method is applied on a road vehicle model to show the effectiveness of the algorithm.