Pulse-Based Control Using Koopman Operator Under Parametric Uncertainty

TL;DR

This paper develops pulse-based control strategies using Koopman operator theory to handle parametric uncertainties in monotone systems, providing convergence time estimates and extending applicability to non-monotone systems.

Contribution

It extends pulse-based control methods with Koopman operator techniques to uncertain systems, offering worst-case convergence estimates and broader applicability.

Findings

Effective control under parametric uncertainty demonstrated.

Provided worst-case convergence time bounds.

Applied methods to genetic toggle switch system.

Abstract

In applications, such as biomedicine and systems/synthetic biology, technical limitations in actuation complicate implementation of time-varying control signals. In order to alleviate some of these limitations, it may be desirable to derive simple control policies, such as step functions with fixed magnitude and length (or temporal pulses). In this technical note, we further develop a recently proposed pulse-based solution to the convergence problem, i.e., minimizing the convergence time to the target exponentially stable equilibrium, for monotone systems. In particular, we extend this solution to monotone systems with parametric uncertainty. Our solutions also provide worst-case estimates on convergence times. Furthermore, we indicate how our tools can be used for a class of non-monotone systems, and more importantly how these tools can be extended to other control problems. We illustrate our approach on switching under parametric uncertainty and regulation around a saddle point problems in a genetic toggle switch system.