Design and validation of a reconfiguration strategy for a redundantly actuated intelligent autonomous vehicle

This paper deals with the reconfiguration of an intelligent autonomous vehicle that utilizes an automatic navigation method and online supervision system and thus can be used to improve the safety, traffic management and space optimization inside the confined space of a port. The bond graph model of the vehicle’s dynamic system is developed in a modular and hierarchical modelling environment. An over-actuated intelligent autonomous vehicle with redundant actuators has four independent driven wheels, four independent braking wheels and a four-wheel steering system. This vehicle can be safely operated with appropriate control law restructuring even when some of its actuators are unusable due to a fault. For actuator fault detection, analytical redundancy relations, which are constraint relations that describe nominal system behaviour and are written in terms of the measured system variables, are derived from the bond graph model. Analytical redundancy relations are continuously evaluated to generate residual signals and the symptoms in these signals are monitored for actuator fault detection and isolation. Once one or more actuator faults are isolated, the system is reconfigured via the selection of an appropriate operating mode to prevent critical or accidental situations. This procedure is validated by considering a fault scenario with two reconfiguration options.