A Robust Decentralised Strategy for Multi-Task Control of Unmanned Aerial Systems. Application on Underactuated Aerial Manipulator

These days we demand Unmanned Aerial Systems (UASs) fly autonomously and be able to physically interact with their environment executing prescribed tasks. An excellent example of that are the Aerial Manipulators (AMs) i.e. UASs formed by the join of an Unmanned Aerial Vehicle (UAV) and a Robot Manipulator (RM). Moreover, the lack of structured workspaces in outdoor operations is challenging for the control system, forcing to increase notably its complexity to meet such requirements but keeping in mind the trade-off between the task performance and computational burden. In this work, a nonlinear control strategy is proposed and thoroughly tested on an AM. The strategy combines the use of robust controllers separately for both UAV and RM exploiting their stability margins to optimise different prescribed criteria in real time. The inclusion of this optimisation in the loop shows excellent results, sharing priorities of the controllers as required. Following this idea, two different strategies have been tested in a benchmark system showing promising results and, furthermore, feasible for a subsequent implementation in the available platform.