Distributed sliding-mode formation control using recurrent interval type 2 fuzzy neural networks for uncertain multi-ballbots

This paper presents a distributed consensus formation control using recurrent interval type-2 fuzzy neural networks (RIT2FNN) for a team of uncertain ballbots. The dynamic equations of each ballbot in sagittal and coronal planes can be decomposed into two identical second-order underactuated dynamic system models, and the multirobot system is modeled by graph theory. By online learning the system uncertainties using RIT2FNN and the Lyapunov stability theory, an intelligent distributed consensus formation control law is presented to carry out formation control in the presence of uncertainties. Simulations are conducted to show the effectiveness and merits of the proposed method.

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