An Underactuated Control System Design for Adaptive Autopilot of Fixed-Wing Drones

Effective design of autopilots for fixed-wing unmanned aerial vehicles (UAVs) is still a great challenge, due to unmodeled effects and uncertainties that these vehicles exhibit during flight. Unmodeled effects and uncertainties comprise longitudinal/lateral cross-couplings, as well as poor knowledge of equilibrium points (trimming points) of...

Adaptive Integral Sliding Mode Control in the Presence of State-Dependent Uncertainty

Adaptive integral sliding mode control (AISMC) is an extension of adaptive sliding mode control which is a way to ensure sliding motion while handling system uncertainties. However, conventional AISMC formulations require to different extent a priori knowledge of the system uncertainty: either the upper bound of the uncertainty or of its time...

Embedding Adaptive Features in the ArduPilot Control Architecture for Unmanned Aerial Vehicles

The operation of Unmanned Aerial Vehicles (UAVs) is often subject to state-dependent alterations and unstructured uncertainty factors, such as unmodelled dynamics, environmental weather disturbances, aerodynamics gradients, or changes in inertia and mass due to payloads. While a large number of autopilot solutions have been proposed to operate...

Cyclic communication in adaptive strategies to platooning: the case of synchronized merging

Recently proposed adaptive platooning strategies for connected automated vehicles are able to cope with uncertain vehicle parameters (uncertain driveline time constants), but can handle only acyclic graphs like look-ahead graphs. This prevents from enhancing platooning protocols with synchronized merging maneuvers, where cyclic communication...