Modeling and control of a class of aerial robotic systems

Abstract

The objectives of this thesis are to propose a new linear uncertain model with bounded uncertainties for an Unmanned Aerial Vehicle (UAV) helicopter system and to propose two new advanced nonlinear kernel controls for the UAV helicopter flight control system using the newly obtained linear uncertain model. The two new control algorithms are based on the Model Following Variable Structure Control (MFVSC) and the deterministic control. They are able to cope with system parameters variations due to the different flight conditions. The first proposed controller is the deterministic control approach augmented MFVSC. The second proposed controller is the deterministic control approach augmented MFVSC with nonlinear state feedback control. Two theorems have been derived based on the two newly developed control algorithms. The two theorems are stable in terms of the second method of Lyapunov provided that the assumptions for the proposed theorems are satisfied. Extensive simulations with different flight conditions and various controller design parameters have been carried out in this study to evaluate the performance and the robustness of the two new control techniques. The simulation results show that the two proposed control algorithms are capable of rendering the system state to track the desired state motion.