Effective dose delivery in atmospheric pressure plasma jets for plasma medicine: A model predictive control approach

Dogan Gidon, David B. Graves, Ali Mesbah

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

Atmospheric pressure plasma jets (APPJs) have been identified as a promising tool for plasma medicine. This paper aims to demonstrate the importance of using model-based feedback control strategies for safe, reproducible, and therapeutically effective application of APPJs for dose delivery to a target substrate. Key challenges in model-based control of APPJs arise from: (i) the multivariable, nonlinear nature of system dynamics, (ii) the need for constraining the system operation within an operating region that ensures safe plasma treatment, and (iii) the cumulative, nondecreasing nature of dose metrics. To systematically address these challenges, we propose a model predictive control (MPC) strategy for real-time feedback control of a radio-frequency APPJ in argon. To this end, a lumped-parameter, physics-based model is developed for describing the jet dynamics. Cumulative dose metrics are defined for quantifying the thermal and nonthermal energy effects of the plasma on substrate. The closed-loop performance of the MPC strategy is compared to that of a basic proportional-integral control system. Simulation results indicate that the MPC stategy provides a versatile framework for dose delivery in the presence of disturbances, while the safety and practical constraints of the APPJ operation can be systematically handled. Model-based feedback control strategies can lead to unprecedented opportunities for effective dose delivery in plasma medicine.

Original languageEnglish (US)
Article number085005
JournalPlasma Sources Science and Technology
Volume26
Issue number8
DOIs
StatePublished - Jul 26 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Condensed Matter Physics

Keywords

  • atmospheric pressure plasmas
  • dose delivery
  • feedback control
  • model predictive control
  • plasma medicine

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