Control of Multistability through Local Sensitivity Analysis: Application to Cellular Decision-making Networks

TL;DR

This paper introduces a local sensitivity analysis approach to control multistable dynamical systems, enabling manipulation of basin properties with computationally efficient signals, applicable to biological and physical systems.

Contribution

It develops sensitivity rules for controlling basin size and depth in multistable systems, offering a novel, cost-effective method for influencing system stability.

Findings

Sensitivity rules effectively control basin properties.

Control signals are computationally inexpensive.

Method provides counter-intuitive insights into parameter influence.

Abstract

Control of multistable dynamical system has important applications, from physics to biology. Here, we attack this problem from the perspective of local sensitivity analysis. We develop sensitivity rules to control properties of continuous-time multistable dynamics with simple attractors, namely, the relative size and depth of their basins of attraction. Our parameter control signal is computationally cheap and provides counter-intuitive information about the sensitive parameters to be manipulated in an experimental setting.