On the use of on-line approximators for sensor fault diagnosis

This paper describes a sensor fault diagnosis algorithm for a class of nonlinear dynamic systems. The main idea behind this approach is to monitor the closed-loop system for any off-nominal system behavior due to sensor faults utilizing a nonlinear online approximator with adjustable parameters. A nonlinear estimation model and learning algorithm are described so that the online approximator provides an estimate of the sensor fault. The robustness, stability and learning performance properties of the nonlinear sensor fault diagnosis scheme are established.