In the present work, the authors were focused on control modes used in distributed microsystems. Especially, they studied distributed manipulation like motion active surface that have been an important topic in micro and nanofabrication field. After comparing advantages and drawbacks between centralized, decentralized and distributed control systems, they decided to apply the control mode to an airflow active surface based on pneumatic microactuator array, and fabricated by MEMS technology. The size of the device is about <i>35x35 mm<sup>2</sup></i> for <i>560</i> MEMS-based actuators and holes respectively at the front- and the back-side of the silicon substrate. In a first approach, and to overcome fabrication problems of the micro-smart system, combining electronic and electro mechanic elements, a co-design software/hardware solution was implemented. By this way, and using a digital image captured from a CCD camera, autonomy of the distributed microsystems could be developed. Afterward, a feedback control strategy was elaborated by applying principles of autonomous mobile robots that lend it to. A first prototype, validating all control mode principles was successfully implemented directly in software. Experiment results demonstrated advantages and good performances of the method.
In this paper, the authors proposed to study a model and a control strategy of a two-dimensional conveyance system based on the principles of the Autonomous Decentralized Microsystems (ADM). The microconveyance system is based on distributed cooperative MEMS actuators which can produce a force field onto the surface of the device to grip and move a micro-object. The modeling approach proposed here is based on a simple model of a microconveyance system which is represented by a 5 x 5 matrix of cells. Each cell is consisted of a microactuator, a microsensor, and a microprocessor to provide actuation, autonomy and decentralized intelligence to the cell. Thus, each cell is able to identify a micro-object crossing on it and to decide by oneself the appropriate control strategy to convey the micro-object to its destination target. The control strategy could be established through five simple decision rules that the cell itself has to respect at each calculate cycle time. Simulation and FPGA implementation results are given in the end of the paper in order to validate model and control approach of the microconveyance system.