Background and activities

Andreas Wenz has graduated from the Karlsruhe Institute of Technology in 2014 with a Master degree in electrical engineering and information technologies. During his studies he has focused mainly in control engineering and signal processing. In his Master's thesis "Prediction of a driver's behaviour using Motion-Tracking sensors", Andreas studied the use of classification methods to predict lane change maneuvers of a driver.

The title of Andrea's Phd project is "Fault tolerant control and automatic de-icing for unmanned aerial vehicles". When operating UAVs in cold and wet climate icing can occur on leading edges of the aircraft. This results in increased drag and weight as well as reduced lift of the UAV.

To prevent this two steps are necessary:

  • Autonomous detection of icing and other faults, using fault detection and isolation (FDI) methods
  • Control strategy to de-ice the UAV by heating while minimising energy consumption

The aim of this project is to create an icing detection system which destinguishes between structural faults caused by icing and other faults like sensor and actuator faults. This will result in an novel fault tolerant UAS control system that reconfigures and replans the mission if necessary.

Scientific, academic and artistic work

Displaying a selection of activities. See all publications in the database


  • Wenz, Andreas Wolfgang; Johansen, Tor Arne. (2016) Icing detection for small fixed wing UAVs using inflight aerodynamic coefficient estimation. Proceedings of 2016 IEEE Conference on Control Applications (CCA).
  • Wenz, Andreas Wolfgang; Johansen, Tor Arne; Cristofaro, Andrea. (2016) Combining model-free and model-based angle of attack estimation for small fixed-wing UAVs using a standard sensor suite. 2016 International Conference on Unmanned Aircraft Systems (ICUAS).