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.
Decentralized Direct MRAC of a Self-Balancing Robot Mounted on a Ball
01.11.2017
879161 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
A Decentralized MRAC-based PSS for Multimachine Power Systems
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