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

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.

Activation of the Normal Human Skin Cells by a Portable Dielectric Barrier Discharge-Based Reaction-Discharge System of a Defined Gas Temperature

“…These reaction-discharge systems include dielectric barrier discharges (DBDs) [14,15], corona discharges (CDs) [37], microwave-induced plasmas (MIPs) [11,12], and plasma jets named kINPen [5,[7][8][9][10]17] or COST [38,39], in addition to the non-thermal atmospheric pressure plasma jets studied and utilized by e.g. Rad et al [40], Gidon et al [41,42], Darmawati et al [43], Cheng et al [44], Busco et al [45]. To be applied in biological systems, the reaction-discharge systems should provide a low gas temperature, i.e., less than 40 °C, along with the controlled production of reactive chemical compounds such as ROS and RNS, and the emission of UV radiation [9].…”

Spatial thermal dose delivery in atmospheric pressure plasma jets

“…We have recently demonstrated the usefulness of modelbased feedback control for mitigating the effects of variabilities and disturbances on APPJ operation [20,22,23]. In this article, we address the problem of uniform delivery of thermal dose of a kHz-excited APPJ in helium along its translation trajectory.…”

Sim-to-real transfer reinforcement learning for control of thermal effects of an atmospheric pressure plasma jet

“…The complexity of APPJ-substrate interactions and disparity of the timescales of physical phenomena make physics-based models of APPJs challenging to develop and time-consuming to solve. However, the dynamics of the thermal response of substrates to APPJs can be reasonably described by lumped-parameter models based on volume averaged mass and energy balances [17]. Here, we conduct a volume-averaged energy balance on the substrate in contact with the APPJ to describe the dynamics of the maximum substrate temperature T s , Here, ⇢, c p and k are the density and heat capacity and thermal conductivity of borosilicate glass, our nominal substrate.…”

“…These variations can result in thermal damage to sensitive substrates [15] and, in general, complicates the delivery of safe and therapeutically e↵ective treatment. All these complexities necessitate model-based feedback control methods for reliable APPJ operation [16][17][18][19].…”