Experimental application of extended Kalman filtering for sensor validation

A sensor failure detection and identification scheme for a closed loop nonl inear system is described in this paper. Detection and identification tasks are performed by estimating parameters directly related to potential failu res. An extended Kalman filter is used to estimate the fault-related parame ters, while a decision algorithm based on threshold logic processes the par ameter estimates to detect possible failures. For a realistic evaluation of its performance, the detection scheme has been implemented on an inverted pendulum controlled by real-time control software. The failure detection an d identification scheme is tested by applying different types of failures o n the sensors of the inverted pendulum. Experimental results are presented to validate the effectiveness of the approach.