School of Engineering
Kirkham Building, KM 001
PhD title: Fault Tolerant Flight Control Systems for Unmanned Aircraft Systems using Artificial Neural Network Framework
'In recent years there has been a significant growth in the development of Unmanned Aerial Vehicles (UAVs) for various applications. UAVs are most commonly used in applications that are considered dangerous, dull, impractical or unreachable by manned vehicles. These applications have contributed to the increasing importance for UAVs and the need to improve their endurance. Increasing the endurance of a UAV allows for:
Longer flight hours without the need to refuel/recharge.
Autonomously maintain stability despite varying environment conditions.
Autonomously maintain stability in case of failure.
This project proposes the development of a robust and adaptive Fault Tolerance Flight Control System (FTFCS) using an Artificial Neural Network (ANN) framework, to improve the endurance of the UAV.
Fault tolerant flight controls systems (FTFCS) are systems that have the ability to tolerate component failures automatically while maintaining overall system stability and acceptable performance in the event of errors and failures. Their purpose is to detect, identify and accommodate for any type of failure that may occur during a flight. Two recognised classes of critical failure are sensor and actuator failures. In general a fully fault tolerant flight control systems needs to perform:•
Sensor Failure Detection, Identification and Accommodation (SFDIA)
Actuator Failure Detection, Identification and Accommodation (AFDIA)'
Prof Joe Howe
Dr Maizura Mokhtar
Mokhtar, M., Bayo, S. Z., Hussain S., Howe, J. M.,"Adaptive and Online Health Monitoring System for Autonomous Aircraft", AIAA Guidance, Navigation, and Control Conference, Minneapolis, Minnesota, 2012.
BEng(Hons) Robotics and Mechatronics, University of Central Lancashire
Institute of Electrical and Electronics Engineers (IEEE), Student Member
Institution of Engineering and Technology (IET), Student Member