AbstractsEngineering

This thesis deals with the development of Adaptive Incremental Backstepping control laws for a high-performance aircraft model (F-16), in order to make the airplane robustly seek references in roll rate and angle of attack at a constant airspeed while minimizing sideslip. An Incremental Backstepping scheme that relies on estimates of the angular accelerations and measurements of the current control deflections is used to reduce the dependency on the on-board aircraft model. The contribution of this thesis is the design and evaluation of three parameter estimators to handle the remaining uncertainties. The estimators that are evaluated in this research are based on Tuning Functions, Least-Squares and Immersion & Invariance. It is shown that the Incremental Backstepping controller is not only more robust to uncertainties in the system dynamics compared to Backstepping, but is also more robust to uncertainties in the control effectiveness matrix. Furthermore, by augmenting the Incremental control law with on-line parameter update laws, the tracking performance of the uncertain F-16 model is significantly increased. The results of this study show the great potential of Adaptive Incremental Backstepping control in increasing the survivability of damaged aircraft.