Sliding mode observer-based fault detection and isolation

Abstract

This chapter considers fault detection and isolation (FDI) for nonlinear systems with uncertainties using particular sliding mode observers for which the parameters can be obtained using LMI techniques. A sliding mode observder-based approach is presented to estimate system faults using bounds on the uncertainty, and as a special case, a fault reconstruction scheme is available where the reconstructed signal can approximate the fault signal to any accuracy. Sensor FDI for nonlinear systems is considered where a nonlinear diffeomorphism is introduced to exploit the system structure and a simple filter is presented to ‘transform’ the sensor fault into a pseudo-actuator fault scenario. Both fault estimation and reconstruction are considered. Case studies on a robotic arm and a mass–spring system are given to demonstrate the effectiveness of the proposed schemes.