Unmanned Aerial Vehicles

Abstract

The multi-DOF dynamic model of unmanned aerial vehicles (UAVs) is a highly nonlinear one and its control can be performed again with (i) global linearization control methods, (ii) local linearization control methods and (iii) Lyapunov analysis-based methods. In approach (i) the dynamic model of the UAV is transformed into an equivalent linear description through the application of a change of variables (diffeomorphisms). In (ii) the nonlinear model of the UAV is decomposed into local linear models for which linear feedback controllers are designed and next the aim is to select the feedback control gains so as to assure the global asymptotic stability of the control loop. In (iii) the objective is to define an energy function for the UAV (Lyapunov function) and to demonstrate that through suitable selection of the feedback control the first derivative of the energy function is always negative and thus the global stability of the control loop is assured. The latter approach is particularly suitable for model-free control of UAVs and takes the form of adaptive control methods. This chapter analyzes the aforementioned control approaches for UAVs and proves global asymptotic stability for all considered control approaches (i) to (iii). The robustness of the aforementioned control methods to model uncertainty and external perturbations is confirmed. Besides elaborated nonlinear filtering approaches are developed that allow for accurate estimation of the state vector of the UAVs through the processing of measurements coming from a limited number of sensors. In particular this chapter treats the following topics: (a) Control of UAVs based on global linearization methods, (b) Control of UAVs based on approximate linearization methods.