Optimal Experimental Design for Uncertain Systems Based on Coupled Differential Equations
This work addresses a domain-specific problem for researchers in control theory and dynamical systems, focusing on incremental improvements in experimental design for uncertain systems.
The paper tackles the optimal experimental design problem for an uncertain Kuramoto model of interacting oscillators, aiming to reduce uncertainty in coupling strengths to minimize robust control costs, and demonstrates the importance of quantifying operational impact in designing such experiments.
We consider the optimal experimental design problem for an uncertain Kuramoto model, which consists of N interacting oscillators described by coupled ordinary differential equations. The objective is to design experiments that can effectively reduce the uncertainty present in the coupling strengths between the oscillators, thereby minimizing the cost of robust control of the uncertain Kuramoto model. We demonstrate the importance of quantifying the operational impact of the potential experiments in designing optimal experiments.