A Robust Control Strategy With Perturbation Estimation for the Parrot Mambo Platform

Abstract

This article addresses theoretical and practical challenges associated with a commercially available and ready-to-fly small-scale unmanned aircraft system (UAS) developed by Parrot SA: the Mambo quad rotorcraft. The dynamic model and the structure of the controller running onboard the UAS autopilot are not disclosed by its manufacturers. For this reason, a novel robust controller for discrete-time systems under time delays and input saturation is first developed for this platform. Then, three fundamental estimation and control challenges are addressed. The first challenge is the system identification of the X and Y translational dynamics of the UAS. To accomplish this goal, input-output data pairs are collected from different UAS platforms during real-time experimental flights. A group of dynamic models are identified from the data pairs through an extended least-squares algorithm. The obtained models are similar in nature but exhibit parametrical variations due to uncertainties in the fabrication process and different levels of wear and tear. Using a time-varying modeling approach, the second challenge addresses the development of a robust controller, which guarantees the stability of all the identified dynamic models. The third challenge addresses the development of a nonlinear controller enhanced with a perturbation estimation, which can reject, from the nominal model, the effects of model uncertainties and perturbations. These theoretical developments are presented in the form of two original theorems. The proposed strategies are ultimately validated in a set of real-time experiments, demonstrating their effectiveness and applicability.