Fault tolerant self-reconfigurable waypoint guidance for mobile robots under actuator faults

This paper presents a fault-tolerant adaptive waypoint guidance algorithm for a four-wheel-drive mobile robot that implements model-based fault detection, isolation (FDI), and reconfiguration. A backstepping controller with optimal gains are designed for waypoint tracking to deal with actuator saturation and uncertainties in the presence of faults. This proposed approach guarantees an optimal actuation signal required for each wheel and simultaneously considers the actuator constraints. The analytical redundancy relations (ARRs) are derived from the mobile robot’s bond graph (BG) model and are used to detect and isolate actuator faults. Simulations and experimental test validate the effectiveness of the FT-AG algorithm. The obtained results demonstrate that the proposed controller can successfully reconfigure itself in response to faults, ensuring continued waypoint tracking with minimal deviation from the desired path.