Abstract

This paper presents an intelligent adaptive steering control using backstepping, aggregated hierarchical sliding-mode control approach and fuzzy basis function networks (FBFN) for seatless electric unicycles. The backstepping hierarchical sliding-mode control approach is used to simultaneously achieve self-balancing and speed control, while the FBFN is employed to on-line learn uncertainties caused by different riders and unknown frictions between the wheel and the terrain surfaces. The performance and merit of the proposed method are well exemplified by conducting two simulations on a laboratory-built electric unicycle. Experimental results show consistent steering performance of the proposed controller for distinct riders and terrain surfaces.

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