Abstract

This paper describes how observer-based techniques for intelligent fault detection were applied to monitoring an active suspension control system in an experimental articulated heavy vehicle. The aim was to define a practical method for detecting faults, taking into account the nonlinearities of the vehicle. The experimental vehicle was divided conceptually into subsystems, namely the passive dynamics of the trailer, the dynamics of the hydraulic actuators, and the expected response of the closed-loop system. A linear dynamic model was designed for each subsystem. A fault detection observer was then designed for each dynamic model. The observer feedback gains were chosen to optimise estimation by the observer residual of specified errors on the output measurements. The observer residuals were then normalised and combined logically to provide a fault diagnosis. The performance of the fault detection scheme is demonstrated in the case of sensor faults and changes in the operation of the active control system.

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