Electrophoresis-Based Adaptive Tube Model Predictive Control of Micro- and Nanoparticles Motion in Fluid Suspension

In this paper, we present an adaptive tube model predictive control (MPC) scheme for the simultaneous manipulation of multiple micro- and nanoparticles using the precisely controlled electric field of a microfluidic device. Unknown variations of the particles’ mobilities and external disturbances are considered. The proposed strategy estimates the unknown mobilities of the particles online using the set membership identification method. Based on the estimate, the dynamic tubes of individual particles are constructed and used in the tube MPC to simultaneously position multiple particles while satisfying constraints. The manipulability and performance of the proposed controller are analyzed. Experimental results validate the effectiveness of the controller to precisely, independently, and simultaneously manipulate multiple particles. The proposed scheme addresses the coupled actuation from the global electric field with separated dynamic tubes constructed for each particle.