Adaptive Tube Model Predictive Control for Manipulating Micro- and Nanoparticles in Fluid Suspensions Under Global External Fields

Global external fields are commonly used to manipulate micro- and nanoparticles in fluid suspension. However, the wireless external actuation has global and coupled influences in the workspace, which limit the robust, independent, and simultaneous control of multiple micro- and nanoparticles. Parametric uncertainty in the particles’ motion model and disturbance make it difficult to steer multiple particles precisely. In this paper, an adaptive tube model predictive control (MPC) scheme is proposed to simultaneously control multiple micro- and nanoparticles in fluid suspensions. The control strategy addresses coupled input actuation from the global electric fields. The unknown mobilities of the particles are continually estimated online, which enables the construction of dynamic tubes of individual particles. The recursive feasibility and the input-to-state stability (ISS) of the scheme are proven. The manipulability of the electrophoresis-based microfluidic manipulation system is quantified and analyzed. The manipulability is affected by the dimensions of the actuating electrodes, the number of particles to be simultaneously and independently controlled, and the configurations of those particles in the microfluidic device. The scalability of the lattice-shaped distributed array of electrodes is discussed. Simulation and experimental results validate the effectiveness of the controller to manipulate multiple particles precisely, independently, and simultaneously.
Note to Practitioners
—To enable the enormous potential of manufacturing functional micro- and nanodevices, it is crucial to automate the steering and manipulation of multiple micro- and nanoparticles. Wireless actuation is a promising way to position those objects in fluid suspensions. However, the global and coupled influences from the wireless external actuation, the parametric uncertainty in the particles’ motion model, and the external disturbances from the fluid flow limit the robust, independent, and simultaneous control of multiple micro- and nanoparticles. In this paper, we present an adaptive tube model predictive control (MPC) scheme to simultaneously control multiple micro- and nanoparticles in fluid suspensions using electric fields. The scheme estimates the unknown mobilities of the particles, constructs dynamic tubes online, and addresses the coupled actuation from the global electric field. The manipulability of the electrophoresis-based microfluidic manipulation system is introduced, quantified, and analyzed. Those analyses give insights into designing the most effective electrode array and the efficient trajectories to achieve agile particle motions. Experimental results validate the manipulability analyses and the performance of the proposed control strategy.