Bond Graph Model Based on Structural Diagnosability and Recoverability Analysis: Application to Intelligent Autonomous Vehicles

A controlled system can be subjected to faults, which may cause unexpected system dynamics that prevent the system objectives to be achieved. This paper introduces the problem of structural fault-tolerance analysis of actuator, sensor, and plant faults with respect to diagnosability and recoverability conditions. Existing methods in the literature usually investigate the fault tolerance of systems separately from fault diagnosis, even if they are strongly related. The bond graph (BG) tool is an adequate tool for dynamic modeling of complex systems and performing fault detection and isolation. The innovative interest of the proposed approach is to extend the use of this tool for verification of structural recoverability conditions by exploiting the behavioral, structural, and causal properties of the BG tool. The obtained structural technique is then applied to an intelligent autonomous vehicle named RobuCar with decentralized inputs and outputs.