In the last few decades the majority of research communities have been pursuing "small world" science and technology. Nanotechnology and smart materials communities have been exploring technologies for constructing and manipulating tiny building blocks that exhibit novel functionality. Biochemistry and biological engineering deal with molecular-level behavior of living cells. To attain meaningful functions out of these tiny building blocks, however, it is necessary to deal with "collective behavior" of vast numbers of tiny things. The challenge is to fill the void between the tiny world and macro-level systems that perform meaningful functions. The major objective of this NSF project is to develop a novel methodology for bridging the gap between the two. Collective behavior of vast numbers of independent units, called cellular systems, will be investigated and controlled based on a stochastic control method inspired by biological systems. Unlike today's engineered artifact, cells in a biological system are not deterministic. Cells are innervated through biochemical diffusion processes, which are fundamentally stochastic. The individual behavior of a single cell is therefore a random process. Nonetheless, the collective ensemble behavior of vast numbers of cells is highly coordinated and reliable. Considering the limited amount of communication and control commands that individual cells receive, this is an amazing behavior, which we would like to explore for effective manipulation of vast cellular systems. To this end, the proposed project presents two key concepts, "stochastic recruitment" and "broadcast feedback", which would demystify ensemble behavior of vast cellular systems. In this stochastic control system, a central controller observes an aggregate output of the cellular units, compares the output to a commanded input, and broadcasts the discrepancy to all the cells uniformly. Instead of demanding the individual cells to obey deterministic commands, the proposed controller only informs the cells about the aggregate error through a global broadcast channel, leaving the final control decision to the individual cells. Each cell, receiving the same aggregate error signal, flips a coin to make a control decision stochastically. Unlike a standard coin, however, the probabilities of heads and tails are modulated with the broadcast signal. This in turn allows the whole cellular system to track a desired aggregate output trajectory. The ensemble behavior of the overall system, although not deterministic, is highly predictable and reliable. Although a large fraction of the cells are dead or non functional, the overall system is still capable of performing the task. The proposed control method has a number of high-impact application areas. A new type of muscle actuators consisting of numerous tiny actuator cells will be developed based on the proposed control. This stochastic control has the potential to be an effective approach to biological process control for angiogenesis and tissue engineering as well as to swarm robot control for environment protection and monitoring. Collaborative research will be explored broadly across the bioengineering, robotics, and control communities during this NSF project. Educational components of the project will include development of new inter-university graduate subjects on stochastic cellular control and K-12 outreach efforts.
