Intelligent adaptive steering control using IT2FNN for uncertain seatless electric unicycles

Abstract

This paper presents an intelligent adaptive steering control using backstepping aggregated hierarchical sliding-mode control approach and interval type 2 fuzzy neural networks (IT2FNN) for uncertain electric seatless unicycles. The backstepping hierarchical sliding-mode control approach is used to simultaneously achieve self-balancing and speed control, and the IT2FNN 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 one simulation on a laboratory-built electric unicycle for distinct riders and terrain surfaces. One experimental result shows the applicability of the proposed controller.