Fuzzy control based on LMI approach and fuzzy interpretation of the rider input for two wheeled balancing human transporter

Abstract

This paper presents a novel hierarchy intelligent control scheme for a two-wheeled human transportation vehicle which is similar to an inverted pendulum. As a high-level supervisory piloting scheme, the paper presents a fuzzy intelligent interpretation of the rider's body inclination. It provides an interface between human user and the vehicle with the aim to enhance the piloting capabilities and convenience from human user viewpoint. As a direct controller, considering the nonlinearities of the system, Takagi-Sugeno fuzzy model is proposed to combine linearized systems and their controllers, where the controller gains of each linear system are optimally obtained by LMI method. The effectiveness of the proposed approaches is verified by applying them on the nonlinear model of the system.