System Design and Inverse Dynamic Problems

System Design and Inverse Dynamic Problems leverage advanced computational methods to model, analyze, and optimize complex systems. By utilizing physics-informed machine learning and temporal logic, we develop robust frameworks that integrate physical laws with logical specifications for accurate and interpretable solutions.

We focus on topics about Physics-Informed Machine Learning Models, Temporal Logic-Based System Design, and Dynamic Problem Solving in Engineering Systems.

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Result

Control/physical systems co-design with spectral temporal logic specifications and its applications to MEMS
Gang Chen, Zhaodan Kong, Longhan Xie
International Journal of Control,2024
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