(239f) Simulation Studies of Active Control Strategy for Sort-Synchronization of Droplets in a Microfluidic Loop Device Using Model Predictive Control

Maddala, J. - Presenter, Texas Tech University
Srinivasan, B. - Presenter, Columbia University
Bithi, S. S. - Presenter, Texas Tech University
Vanapalli, S. A. - Presenter, Texas Tech University
Rengaswamy, R. - Presenter, Texas Tech University

Research and development in the field of droplet microfluidics has increased tremendously in recent years. Droplet microfluidics finds applications in several fields such as protein crystallization, biochemical assays, high throughput screening of cells, fabrication of micro and nano particles, chemical reactors and biosensors. These applications require controlled behaviors of droplets in a network of confined channels. For instance, sorting and synchronization of droplets in a microfluidic device are important operations. Sorting is the task of reliably alternating the droplet movement to the upper and lower arms. Synchronization requires that the droplets at the upper and lower arms exit the loop at the same time. Complex nonlinear dynamic behaviors of the droplets in the microfluidic devices pose difficulties in achieving such sort-synchronization. In the literature both passive and active control strategies have been reported for this problem.

In this talk, we discuss a first attempt at using a model based control algorithm for active control of droplets in a loop device for sort-synchronization. The proposed model predictive control (MPC) algorithm takes into account the nonlinear dynamics of the droplets using a network model available in literature. The MPC algorithm manipulates the resistances in the two arms of the loop to achieve sort-synchronization. Realistic constraints arising due to micro-valve actuation are handled in the control algorithm and practical guidelines are provided for implementation of the MPC algorithm in microfluidic droplet systems. Results for sort-synchronization of droplets obtained at various flow conditions using the MPC algorithm will be presented. The droplets at these flow conditions exhibit: (i) two period, (ii) three period, and (iii) aperiodic Poincare maps. Simulation studies performed demonstrates that it is possible to achieve satisfactory control in all these nonlinear scenarios. Online implementation of this MPC algorithm on an experimental microfluidic loop is of future research interest.