Sliding Mode Observer and State Machine Based Fault Diagnosis With Application in a Vehicle Chassis Steering System

Abstract

A novel fault detection and identification (FDI) scheme based on sliding mode observer (SMO) residual generator and state machine residual evaluator is presented in this paper. The FDI scheme is applied to actuator and sensor faults in a vehicle chassis steering system described by a nonlinear bicycle model with three degrees of freedom. Primary residual is generated by an expanded SMO designed for linear time varying (LTV) systems. To cope with the multiple faults isolation problem, the state machine records and utilizes the previous fault information to determine the current fault state. Simulation results show that multiple fault detection and isolation can be successfully achieved by the proposed SMO and statemachinebased FDI scheme.