Implementation of Fuzzy Inference Engine for equilibrium and roll-angle tracking of riderless bicycle
This work provides a practical implementation of fuzzy control for autonomous bicycle stabilization, but is incremental as it applies existing fuzzy methods to a specific robotic platform.
The paper presents a fuzzy inference system for stabilizing and tracking roll-angle of a riderless bicycle, achieving steady turning and roll-angle tracking through experimental validation.
In this paper, a Fuzzy Inference System (FIS) is fabricated on a riderless bicycle. The Fuzzy Inference System is based on a rule base inherited from human experience of bicycle riding. The steady turning motion and roll-angle tracking controls for the riderless bicycle were achieved by using fuzzy concept. Collection of sensors, actuator, micro-controller and electrical circuits were employed to introduce new prototype autonomous bicycle. Effectiveness of the control scheme was proved by experimental tests and stabilization and roll-angle tracking of the real bicycle was illustrated by results.