System Design and Modeling of a Time-Varying, Nonlinear Temperature Controller for Microfluidics

Abstract

We present a custom-made temperature control system for performing sensitive biochemical reactions within a microfluidic platform. The thermoelectric module (TEM)-based system is part of a microfluidic platform for genetic basis of disease diagnosis. Multistage TEMs with individualized control are used to improve the response speeds compared to a single TEM. Currently, there exists neither a mathematical representation to predict the TEMs' response, nor any standardized approach to identify such systems-both of which will greatly assist in effectively controlling the temperature of the TEMs. Hence, we propose here an approach for system identification of these nonlinear elements in a cascade configuration. In this customized TEM configuration, a linear multiple-input-multi-output (MIMO) structure with temperature difference variables as the system outputs is chosen to derive the system model for subsequent controller design. For the application of temperature cycling between different set-points, a group of model-based controllers with switching strategy is designed, and for each set-point region, an internal model-based decentralized controller is implemented. Both simulation and experimental results demonstrate that the switching controller exhibits superior control performance for fast tracking (~ 6°C/s slew rate) and low steady state error (±0.1°C) when compared to a non-switching controller. The controller design approach can easily be extended to further multi-channel modules for wider applicability. Here, the integration of cost-effective and thermally-efficient physical temperature control elements with a switching and decentralized controller is applied to viral detection, which serves as the validation of the system identification-based controller.