Bifurcation instructed design of multistate machines

TL;DR

This paper introduces a new design paradigm for multistate machines based on bifurcations in energy landscapes, enabling robust, sensitive state transitions controlled by small parameter changes, with applications in soft robotics and microscale systems.

Contribution

It presents a novel bifurcation-based design framework and an efficient algorithm for creating multistate machines with robust transition pathways.

Findings

Demonstrated magneto elastic machines with bifurcation-guided motions

Achieved multiple transition pathways near bifurcations

Showed potential for soft robotics and microscale applications

Abstract

We propose a novel design paradigm for multistate machines where transitions from one state to another are organized by bifurcations of multiple equilibria of the energy landscape describing the collective interactions of the machine components. This design paradigm is attractive since, near bifurcations, small variations in a few control parameters can result in large changes to the system's state providing an emergent lever mechanism. Further, the topological configuration of transitions between states near such bifurcations ensures robust operation, making the machine less sensitive to fabrication errors and noise. To design such machines, we develop and implement a new efficient algorithm that searches for interactions between the machine components that give rise to energy landscapes with these bifurcation structures. We demonstrate a proof of concept for this approach by designing magneto elastic machines whose motions are primarily guided by their magnetic energy landscapes and show that by operating near bifurcations we can achieve multiple transition pathways between states. This proof of concept demonstration illustrates the power of this approach, which could be especially useful for soft robotics and at the microscale where typical macroscale designs are difficult to implement.