Pulse-Based Control Using Koopman Operator Under Parametric Uncertainty
For control engineers working with systems where actuation is limited (e.g., biomedicine, synthetic biology), this work offers a practical method to handle parametric uncertainty in pulse-based control, though it is an incremental extension of existing theory.
This paper extends a pulse-based control method for monotone systems to handle parametric uncertainty, providing worst-case convergence time estimates and demonstrating applicability to non-monotone systems and other control problems on a genetic toggle switch.
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.