Laboratory for Control, Learning, and Systems Biology

linear time-varying systems

2025
  1. D. Biswas, E.D Sontag, N.J. Cowan, "An exact active sensing strategy for a class of bio-inspired systems", European Journal of Control, 2025. wwwpdf
    Also in Proc. 23rd European Control Conference, and longer version in https://arxiv.org/abs/2411.06612.
    Abstract

    We consider a general class of translation-invariant systems with a specific category of output nonlinearities motivated by biological sensing. We show that no dynamic output feedback can stabilize this class of systems to an isolated equilibrium point. To overcome this fundamental limitation, we propose a simple control scheme that includes a low-amplitude periodic forcing function akin to so-called "active sensing" in biology, together with nonlinear output feedback. Our analysis shows that this approach leads to the emergence of an exponentially stable limit cycle. These findings offer a provably stable active sensing strategy and may thus help to rationalize the active sensing movements made by animals as they perform certain motor behaviors.

2009
  1. D. Angeli, P. de Leenheer, E.D. Sontag, "Chemical networks with inflows and outflows: A positive linear differential inclusions approach", Biotechnology Progress, vol. 25, pp. 632-642, 2009. pdf
    Abstract

    Certain mass-action kinetics models of biochemical reaction networks, although described by nonlinear differential equations, may be partially viewed as state-dependent linear time-varying systems, which in turn may be modeled by convex compact valued positive linear differential inclusions. A result is provided on asymptotic stability of such inclusions, and applied to biochemical reaction networks with inflows and outflows. Included is also a characterization of exponential stability of general homogeneous switched systems