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arXiv · 2510.06547

Model Predictive Path Integral Control for Roll-to-Roll Manufacturing

Christopher Martin·Apurva Patil·Wei Li·Takashi Tanaka·Dongmei Chen
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Abstract

Roll-to-roll (R2R) manufacturing is a continuous processing technology essential for scalable production of thin-film materials and printed electronics, but precise control remains challenging due to subsystem interactions, nonlinearities, and process disturbances. This paper proposes a Model Predictive Path Integral (MPPI) control formulation for R2R systems, leveraging a GPU-based Monte-Carlo sampling approach to efficiently approximate optimal controls online. Crucially, MPPI easily handles non-differentiable cost functions, enabling the incorporation of complex performance criteria relevant to advanced manufacturing processes. A case study is presented that demonstrates that MPPI significantly improves tension regulation performance compared to conventional model predictive control (MPC), highlighting its suitability for real-time control in advanced manufacturing.

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Christopher Martin, Apurva Patil, Wei Li, Takashi Tanaka, Dongmei Chen. 2025-10-08. Model Predictive Path Integral Control for Roll-to-Roll Manufacturing. https://doi.org/10.1016/j.ifacol.2025.12.260.

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