Pitchfork-bifurication-based competitive and collaborative control of an E-bike system

TL;DR

This paper introduces a novel control strategy for smart e-bikes using pitchfork bifurcation models to manage human-motor interactions, enhancing disturbance rejection and behavioral control through in vivo experiments.

Contribution

It proposes a pitchfork bifurcation-based control framework combined with gain-scheduling to handle competitive and cooperative human-motor interactions in e-bike systems.

Findings

Effective disturbance rejection demonstrated in vivo.

Successful management of human-motor interaction dynamics.

Enhanced control of cycling behavior metrics.

Abstract

This paper is concerned with the design of a human-in-the-loop system for deployment on a smart pedelec (e-bike). From the control-theoretic perspective, the goal is not only to use the power assistance of the e-bike to reject disturbances along the route but also to manage the possibly competitive interactions between a human and the motor intervention. Managing the competitive/cooperative nature of the interactions is crucial for applications in which we wish to control physical aspects of the cycling behavior (e.g. heart rate and breathing rate). The basis of the control is a pitchfork bifurcation system, modeling the interactions, augmented using ideas from gain-scheduling. In vivo experiments have been conducted, showing the effectiveness of the proposed control strategy.