The paper entitled “Optimal Experimental Design for Uncertain Systems Based on Coupled Differential Equations,” has been published in IEEE Access and is now accessible in the link below:

Youngjoon Hong, Bongsuk Kwon, and Byung-Jun Yoon, “Optimal Experimental Design for Uncertain Systems Based on Coupled Differential Equations,” IEEE Access, doi: 10.1109/ACCESS.2021.3071038.

In this work, a general optimal experimental design (OED) strategy is proposed for an uncertain system that is described by coupled ordinary differential equations (ODEs), whose parameters are not completely known. As a vehicle for developing the OED strategy, this study focuses on non-homogeneous Kuramoto oscillator models, where the objective is the robust control of a given uncertain Kuramoto model to achieve global frequency synchronization.

Illustrative overview of the proposed optimal experimental design (OED) framework.

The proposed OED strategy quantifies the objective uncertainty of the Kuramoto model based on the mean objective cost of uncertainty (MOCU), where the optimal experiment can be identified by predicting the best experiment in the design space that is expected to maximally reduce the MOCU.

This study highlights the importance of quantifying the operational impact of the potential experiments in designing the optimal experiment and it demonstrates that the MOCU-based OED scheme enables one to minimize the cost of robust control of a uncertain Kuramoto model with the fewest experiments compared to other alternatives.

The proposed scheme is fairly general and it can be applied to any uncertain complex system represented by coupled ODEs.

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