460428 Model Predictive Control of Atmospheric Pressure Plasma Jets for Biomedical Applications

Thursday, November 17, 2016: 12:48 PM
Monterey II (Hotel Nikko San Francisco)
Dogan Gidon1, David B. Graves2 and Ali Mesbah1, (1)Department of Chemical and Biomolecular Engineering, University of California - Berkeley, Berkeley, CA, (2)Chemical & Biomolecular Engineering, University of California, Berkeley, Berkeley, CA

Model Predictive Control of Atmospheric Pressure Plasma Jets for Biomedical Applications

D. Gidon, D. B. Graves, A. Mesbah

Department of Chemical and Biomolecular Engineering, University of California Berkeley

E-mail: dgidon@berkeley.edu

Atmospheric Pressure Plasma Jets (APPJs) are a class of cold, ambient pressure plasma devices that are increasingly used for biomedical purposes. Energetic electrons in these plasmas drive the production of therapeutically relevant components such as reactive oxygen and nitrogen species (RONs), UV-range photons, heat, and electric field. However, under atmospheric pressure, the characteristics of the plasma and the associated therapeutic effects can vary drastically with changing environmental conditions and disturbances [1]. Multiple modes observed in both radio frequency (RF) range [2] and kilohertz range [3] excited APPJs exemplifies this phenomenon. The change in plasma behavior is often associated with a heterogeneous, filamentary discharge structure and can lead to ‘arcing’ where all the current is concentrated in a thin conductive plasma channel. This sensitivity of the plasma behavior to external conditions makes reliable and reproducible operation of APPJs difficult, in particular for safety-critical applications. The large amount of heat and current delivered to the treated surface with arcing is also generally undesirable for biomedical applications due to safety considerations. The latter operational considerations and the requirements for high performance and strict constraint handling necessitate application of advanced control strategies for regulating the intricate dynamics of APPJs.

Dynamics of APPJs are commonly described by a set of coupled, high dimensional fluid equations. Small spatial discretization and small time steps are necessary to capture the non-equilibrium behavior of the plasma and the spatial distribution of variables of interest [1]. Consequently, the computational cost associated the solution of such fluid models becomes prohibitive for use in on-line optimal control strategies, such as model predictive control (MPC). Recent developments in analytical and numerical ‘global’ (zero-dimensional) modeling of APPJs [4] have revealed that simpler models can provide adequate descriptions of dynamical characteristics of plasmas. Moreover, for control, such global models must be extended to account for the full complexity of operation; including the electrical circuit associated with the device and the effects of the plasma on the treated surface. These requirements motivate our approach to control-oriented, lumped-parameter modeling of APPJs based on first principles.

In this work, a nonlinear MPC (NMPC) is designed based on a control-oriented lumped parameter model of the argon RF-APPJ reported in [5]. The control-oriented thermal model of the APPJ coupled with a biological surface, presented in [6], is extended by a lumped-parameter equivalent circuit model and a truncated reaction network to adequately represent system physics. The performance of the proposed NMPC approach is evaluated in terms of regulating the target surface temperature and the current delivered to the surface. The closed-loop simulation results of NMPC are compared to those of an internal model control system for various scenarios inspired from biomedical applications of the APPJ under study.


[1] H. W. Lee G. Y. Park, Y. S. Seo, Y. H. Im, S. B. Shim, and H. J. Lee, Journal of Physics D: Applied Physics, 44, 053001 (2011).

[2] J. J. Shi, X. T. Deng, R. Hall, J. D. Punnett, and M. G. Kong, Journal of Applied Physics, 94:10, 6303 (2003).

[3] J. Walsh, F. Iza, N.  B. Jason, V. J. Law, and M. G. Kong, Journal of Physics D: Applied Physics, 43, 075201 (2010).

[4] M. Lieberman, Plasma Sources Science and Technology, 24, 025009 (2015)

[5] S. Hofmann, K. van Gils, S. van der Linden, S. Iseni. P. Bruggeman, European Physical Journal D, 68:3 (2014)

[6] D. Gidon, D. B. Graves, A. Mesbah, Proceedings of the American Control Conference, Accepted, Boston (2016).


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