Slow Computing

This page is being written up for a report on the “Impact of Control,” being edited by Tariq Samad and Anuradha Annaswamy.

Current techniques for the design of software-enabled control systems rely on the existence of high performance sensing, actuation and computational devices that can be embedded within a physical system at modest cost. Driven by Moore's law, the success of this paradigm can be seen through the broad usage of feedback controllers in modern application areas, ranging from transportation to communications to medicine to robotics. The goal of this challenge lies at the other end of the computational spectrum: can we develop new principles and tools for the design of closed loop control systems using highly distributed, but slow, computational elements. The motivation for control design using slow computing is to develop new architectures for feedback control systems that can be used in applications where computational power is extremely limited. One important class of such systems is that for which the energy usage of the system must remain small, either due to the source of power available (e.g. batteries or solar cells) or the physical size of the device (e.g. microscale and nanoscale robots). A longer term application area is in the design of control systems using novel computing substrates, such as biological circuits. A critical element in both cases is the tight coupling between the dynamics of the underlying process and the temporal properties of the algorithm that is controlling it. Design of feedback systems using slow computing is particularly challenging due to the performance limitations placed on systems with computational delays that are comparable to the underlying dynamics. These systems are likely to use highly parallel, non-deterministic architectures to achieve what is normally accomplished through the tightly synchronized, serial interconnections of sensing, filtering, estimation, planning, regulation and actuation that are common in traditional control systems. Unfortunately, current techniques for systematic design of control systems assume a mostly serial processing architecture and techniques that make use of parallel architectures (such as neural networks) do not provide sufficiently systematic design methods. New research is required to develop the architectures, theory and tools required to design controllers where computational delay does not allow current techniques to be utilized.

And There's Much More

Bacterial chemotaxis is just one of many interesting processes implemented using biomolecular feedback systems.