Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

Oakley, Rhianna M.; Polonsky, Andrew T.; Chao, Paul; Danielson, Claus

doi:10.1109/lcsys.2024.3514977

Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

Journal Article · Mon Dec 09 00:00:00 EST 2024 · IEEE Control Systems Letters

DOI:https://doi.org/10.1109/lcsys.2024.3514977· OSTI ID:2498463

^[1]; Polonsky, Andrew T. ^[2]; ^[2]; ^[3]

Univ. of New Mexico, Albuquerque, NM (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Univ. of New Mexico, Albuquerque, NM (United States)

This letter presents a one-step predictive run-to-run controller (R2R-MPC) for the automation of mechanical serial sectioning (MSS), a destructive material analysis process. To address the inherent uncertainty and disturbances in the MSS process, a robust closed-loop approach is presented. Here, the robust R2R-MPC models the uncertainty of the MSS process using a linear differential inclusion. As an analytical model of the MSS process is unavailable, the differential inclusion is identified from historical data. The R2R-MPC is posed as an optimization problem that computes incremental changes to the control input which minimize the worst-case material removal errors. This optimization-based controller is combined with a run-to-run controller to provide integral action that rejects constant disturbances and tracks constant reference removal rates. To demonstrate the efficacy of our robust R2R-MPC, we present simulation results which compare the presented controller with a conventional non-robust R2R.

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This content will become publicly available on Tue Dec 09 00:00:00 EST 2025

Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525

OSTI ID:: 2498463

Report Number(s):: SAND-2025-00056J

Journal Information:: IEEE Control Systems Letters, Vol. 8; ISSN 2475-1456

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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