Dynamic modelling and nonlinear control of vortex-coupled delta wing systems

The first part of this thesis proposes a control-oriented vortex-coupled nonlinear retarded state space representation of free-to-roll motion of a delta wing. Linear, nonlinear and neural network based parameter identification methods have been used to approximate the rolling moment coefficient. Various experimental results validate the proposed model.; In the second part, fast vortex-coupled delta wing roll dynamics with state delay in is controlled using a robust adaptive output feedback control law. The controller has been tested against modelling uncertainties in rolling moment coefficient. The controller is shown to render the delta wing vortex-coupled roll dynamics globally practically stable. Heuristic design process and parameter selection methods have been proposed for easier implementation of this control algorithm. The results of the numerical simulation demonstrate the applicability of this controller for different initial conditions.; The third part proposes a combinatory control strategy combined of a modified state feedback stabilizing controller, as the internal loop, and a robust adaptive sliding tracking controller. The robust adaptive tracking controller utilizes a special gaussian radial basis function network for online estimation of unknown nonlinearity. To show the capability of the proposed combinatory control structure, it has been implemented to the delta wing dynamics to follow a complex reference trajectory. Implementing the proposed combined control structure enhanced the tracking performance in comparison to the controller without internal loop. Adding two more control inputs enhanced the tracking controller performance. The Heuristic design process and parameter selection methods have been proposed for easier implementation of tracking control and combined control structure.