Fault Tolerant Tracking Control of an Unmanned Aerial Vehicle Subject to Actuator Faults

Abstract

In manned control systems, a human operator serves the role of the central integrator of system operations. In autonomous control systems, the control is more challenging for which the control scheme should be robust to external disturbances and faults, in addition to performing the required operations efficiently. In practical situations, Unmanned Aerial Vehicles and other autonomous control systems can face different kinds of faults and failures during operation. A robust scheme has to be designed for detecting and identifying these faults before they lead to permanent failure and damage. This research employs a residual generation scheme based on full-state observer for Fault Detection and Identification (FDI) with application of Eigenstructure assignment for disturbance de-coupling. A hypothesis testing scheme, Sequential Probability Ratio Testing (SPRT), tests the generated residual signals efficiently to make decision about fault in the system. Multiple Model Switching and Tuning (MMST) controllers based on two different schemes are brought into action at the reconfiguration stage to achieve tracking control of roll and yaw angle. Simulations are performed using a lateral directional model of an Aerosonde UAV to show that the propose FDI scheme is robust and efficient and the proposed reconfiguration controllers efficiently track the desired reference signal.