Implementation of Fuzzy Inference Engine for equilibrium and roll-angle tracking of riderless bicycle

TL;DR

This paper presents a fuzzy inference system integrated into a riderless bicycle to achieve stable turning and roll-angle tracking, demonstrating effective autonomous control through experimental validation.

Contribution

It introduces a novel fuzzy inference-based control scheme for autonomous bicycles, utilizing human experience-derived rules and experimental testing for validation.

Findings

Successful stabilization and roll-angle tracking demonstrated

Experimental tests confirm control scheme effectiveness

Prototype autonomous bicycle achieved stable turning

Abstract

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.