Control of IPMC Actuators for Microfluidics With Adaptive ''Online'' Iterative Feedback Tuning

Abstract

Ionic polymer metal composites (IPMCs) are actuators that lend themselves well to microfluidic applications due to their lightweight, flexibility, ability to tailor their geometry, as well as the capability to be miniaturized and implanted into microelectro-mechanical systems devices. The major issue with implementing IPMCs into such devices is the ability to control their actuation and, hence, their reliability over a long period of time. This paper presents a novel iterative feedback tuning (IFT) algorithm that tunes the system online using experimental data during normal system operation. The controller adaptively tunes the highly nonlinear and time varying IPMC for a newly proposed micropump. This demonstrates the ability of the system to have a reliable performance over a long period of time without the need of any offline tuning or system identification. The system was run for 20 controller updates. This corresponds to 10 and 20 min of operation for the 0.1 and 0.05 Hz reference inputs, respectively. 100 and 300 $mu$m amplitudes were tested to demonstrate the ability of the system to adaptively tune to different input signals. Experimental results show the newly proposed IFT algorithm has successfully tuned the controller to achieve up to 92% better performance when compared with a conventional model-based tuned controller.