Current research on Unmanned Aerial Vehicles (UAVs) is focusing on the ability of performing complex tasks by means of cooperation over many aircraft, with the scope of reducing costs and increasing the reliability. However, the use of a cooperative formation deals with several challenges to coordinate a group of autonomous vehicles. A distributed situational awareness becomes an essential requirement towards the objective. In this paper, a Decentralized Moving Horizon Estimator (DMHE) is presented with the scope of distributing the computational burden and limiting the requirements about communication and software complexity besides avoiding the vulnerability of a centralized architecture to faults. The proposed algorithm merges the consensus theory with a moving horizon estimator to overcome Kalman filtering problems in the presence of constraints on any disturbance or state variables. The decentralization of the scheme is obtained by decomposing the overall estimation problem in several optimization sub-models whose convergence is guaranteed by consensus. A preliminary sensitivity analysis was performed to evaluate the results of the proposed strategy and the significance of its main parameters.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Decentralized Moving Horizon Estimation for a Fleet of UAVs


    Contributors:


    Publication date :

    2022-06-21


    Size :

    1738764 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Moving Horizon Estimation of Air Data Parameters for UAVs

    Wenz, Andreas / Johansen, Tor Arne | IEEE | 2020




    DECENTRALIZED COLLISION AVOIDANCE FOR UAVS

    HALL ROBERT J | European Patent Office | 2022

    Free access

    Decentralized collision avoidance for UAVs

    HALL ROBERT J | European Patent Office | 2021

    Free access