Stochastic Recruitment and Broadcast Feedback of Cellular Control Systems and Its Application to Muscle Actuators

在过去的几十年里，大多数研究团体一直在追求“小世界”科学和技术。纳米技术和智能材料社区一直在探索构建和操纵具有新功能的微小构建块的技术。生物化学和生物工程学研究活细胞的分子水平行为。然而，为了从这些微小的构建块中获得有意义的功能，有必要处理大量微小事物的“集体行为”。挑战在于填补微观世界和执行有意义功能的宏观层面系统之间的空白。这个国家科学基金会项目的主要目标是开发一种新的方法来弥合两者之间的差距。大量独立单元的集体行为，称为细胞系统，将被研究和控制的基础上随机控制方法的启发，生物系统。与今天的工程人工制品不同，生物系统中的细胞不是确定性的。细胞通过生化扩散过程受神经支配，这基本上是随机的。因此，单个细胞的个体行为是一个随机过程。尽管如此，大量细胞的集体集合行为是高度协调和可靠的。考虑到单个细胞接收的通信和控制命令数量有限，这是一个令人惊讶的行为，我们希望探索有效操纵庞大的细胞系统。为此，该项目提出了两个关键概念，“随机招募”和“广播反馈”，这将揭开神秘的巨大的蜂窝系统的合奏行为。在该随机控制系统中，中央控制器观察蜂窝单元的总输出，将输出与命令输入进行比较，并将差异均匀地广播到所有单元。而不是要求个别细胞服从确定性的命令，所提出的控制器只通知细胞的聚合误差通过一个全球广播信道，离开最终的控制决策的个别细胞。每一个接收到相同的总误差信号的细胞随机地掷硬币做出控制决策。然而，与标准硬币不同的是，正面和反面的概率是用广播信号调制的。这又允许整个蜂窝系统跟踪期望的聚合输出轨迹。 整个系统的集合行为虽然不是确定性的，但具有高度的可预测性和可靠性。虽然大部分细胞死亡或不起作用，但整个系统仍然能够执行任务。所提出的控制方法具有许多高影响力的应用领域。一种新型的肌肉执行器组成的许多微小的致动器单元将开发基于所提出的控制。这种随机控制有可能成为一种有效的方法，生物过程控制的血管生成和组织工程，以及群体机器人控制的环境保护和监测。在这个NSF项目期间，将在生物工程、机器人和控制社区广泛探索合作研究。该项目的教育部分将包括开发关于随机细胞控制和K-12外联工作的新的大学间研究生课程。

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.