In this paper, a decentralized direct model reference adaptive control (MRAC) scheme is proposed in order to achieve the control for both ball and body dynamics of a self–balancing robot mounted on a ball, also known as ballbot. The nonlinear model for the ballbot is decomposed in the ball dynamics and body dynamics subsystems. Thus, a second order system is defined for each nonlinear dynamical subsystem. Under the assumption that a linear–in–the–parameters model for each second order system can be defined, then each subsystem is represented by a parameterized model from which a local direct MRAC is designed. The performance of our decentralized adaptive control scheme is validated via simulation results taking into account parametric variations, noise in the measurements and external perturbations.


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    Title :

    Decentralized Direct MRAC of a Self-Balancing Robot Mounted on a Ball


    Contributors:


    Publication date :

    2017-11-01


    Size :

    879161 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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