Project Grant 2606020

The National Science Foundation Division of Mathematical Sciences awarded Clemson University $265,000 on August 15, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop data-driven control frameworks for systems governed by partial differential equations.

The research establishes analytical and computational foundations for controlling complex PDE systems across applications including soft robotics, building energy systems, vehicle autonomy, smart manufacturing, and advanced materials. The work constructs a Koopman operator theoretic framework for data-driven optimal control of nonlinear PDE systems, particularly thermoelasticity and multi-flow dynamics interacting with elastic bodies—phenomena relevant to aircraft design, ocean-air interactions, and atmospheric icing events. High-resolution spatiotemporal data collected via distributed sensors on controlled processes such as soft robotic systems will inform the control design methodology, addressing the challenge that physics-based PDE models are difficult to derive accurately given the complex, high-dimensional nature of underlying dynamics.

The project integrates applied mathematics and engineering methodologies, with an educational component training undergraduate and graduate students in an interdisciplinary program bridging theory and application. Students will develop expertise in data science, control theory, dynamical systems, optimization, and robotics.

Performance occurs in Clemson, South Carolina, with an ultimate completion date of July 31, 2029.