Adaptive Tube Model Predictive Control for Manipulating Multiple Nanowires with Coupled Actuation in Fluid Suspension

Abstract

Automated, highly precise online manipulation of multiple nano and microscale objects is essential to achieve scalable nanomanufacturing. One of the biggest limitations of the wireless external actuation is its global and coupled influence in the workspace, which limits the capability to robustly control multiple nano and microparticles independently and simultaneously. Another challenge for the highly precise manipulation of nanoparticles is due to their uncontrolled variations in structures or compositions that result in different dynamic behaviors. In this paper, we present an adaptive tube model predictive control scheme for the simultaneous manipulation of multiple nanowires under coupled electric fields in fluid suspension. The proposed strategy estimates the unknown mobilities of the individual nanowires online, formulates dynamic tubes that update based on the online estimated mobilities and nonlinear dynamics, and addresses the coupled actuation from the global electric field with dynamic separated tubes constructed for each nanowire. Simulations results show that as the number of simultaneously manipulated nanowires increases, the manipulation time increases and the maximum disturbance the system could reject decreases rapidly.