An Optimal Control Formulation of Pulse-Based Control Using Koopman Operator

Abstract In many applications, and in systems/synthetic biology, in particular, it is desirable to solve the switching problem, i.e., to compute control policies that force the trajectory of a bistable system from one equilibrium (the initial point) to another equilibrium (the target point). It was recently shown that for monotone bistable systems, this problem admits easy-to-implement open-loop solutions in terms of temporal pulses (i.e., step functions of fixed length and fixed magnitude). In this paper, we develop this idea further and formulate a problem of convergence to an equilibrium from an arbitrary initial point. We show that the convergence problem can be solved using a static optimization problem in the case of monotone systems. Changing the initial point to an arbitrary state allows building closed-loop, event-based or open-loop policies for the switching/convergence problems. In our derivations, we exploit the Koopman operator, which offers a linear infinite-dimensional representation of an autonomous nonlinear system and powerful computational tools for their analysis. Our solutions to the switching/convergence problems can serve as building blocks for other control problems and can potentially be applied to non-monotone systems. We illustrate this argument on the problem of synchronizing cardiac cells by defibrillation.

[1]  Sanjit A. Seshia,et al.  Directed Specifications and Assumption Mining for Monotone Dynamical Systems , 2016, HSCC.

[2]  Kim Sneppen,et al.  Conditional Cooperativity of Toxin - Antitoxin Regulation Can Mediate Bistability between Growth and Dormancy , 2013, PLoS Comput. Biol..

[3]  Christopher A. Voigt,et al.  Principles of genetic circuit design , 2014, Nature Methods.

[4]  P. Schmid,et al.  Dynamic mode decomposition of numerical and experimental data , 2008, Journal of Fluid Mechanics.

[5]  J. Collins,et al.  Construction of a genetic toggle switch in Escherichia coli , 2000, Nature.

[6]  D. Pincus,et al.  In silico feedback for in vivo regulation of a gene expression circuit , 2011, Nature Biotechnology.

[7]  Alexandre Mauroy,et al.  Converging to and escaping from the global equilibrium: Isostables and optimal control , 2014, 53rd IEEE Conference on Decision and Control.

[8]  S. Yoshizawa,et al.  An Active Pulse Transmission Line Simulating Nerve Axon , 1962, Proceedings of the IRE.

[9]  David Angeli,et al.  Monotone control systems , 2003, IEEE Trans. Autom. Control..

[10]  Aivar Sootla,et al.  Operator-Theoretic Characterization of Eventually Monotone Systems , 2015, IEEE Control Systems Letters.

[11]  Priscilla E. M. Purnick,et al.  The second wave of synthetic biology: from modules to systems , 2009, Nature Reviews Molecular Cell Biology.

[12]  F. Fages,et al.  Long-term model predictive control of gene expression at the population and single-cell levels , 2012, Proceedings of the National Academy of Sciences.

[13]  Mario di Bernardo,et al.  Analysis, design and implementation of a novel scheme for in-vivo control of synthetic gene regulatory networks , 2011, Autom..

[14]  Igor Mezic,et al.  Global Stability Analysis Using the Eigenfunctions of the Koopman Operator , 2014, IEEE Transactions on Automatic Control.

[15]  R. FitzHugh Impulses and Physiological States in Theoretical Models of Nerve Membrane. , 1961, Biophysical journal.

[16]  David Angeli,et al.  Shaping pulses to control bistable systems: Analysis, computation and counterexamples , 2016, Autom..

[17]  I. Mezić Spectral Properties of Dynamical Systems, Model Reduction and Decompositions , 2005 .

[18]  Aivar Sootla,et al.  Properties of isostables and basins of attraction of monotone systems , 2016, 2016 American Control Conference (ACC).

[19]  Mauricio Barahona,et al.  Switchable genetic oscillator operating in quasi-stable mode , 2009, Journal of The Royal Society Interface.

[20]  Steven L. Brunton,et al.  On dynamic mode decomposition: Theory and applications , 2013, 1312.0041.

[21]  I. Mezić,et al.  Isostables, isochrons, and Koopman spectrum for the action-angle representation of stable fixed point dynamics , 2013, 1302.0032.

[22]  I. Mezić,et al.  Analysis of Fluid Flows via Spectral Properties of the Koopman Operator , 2013 .

[23]  Jeff Moehlis,et al.  An Energy-Optimal Methodology for Synchronization of Excitable Media , 2014, SIAM J. Appl. Dyn. Syst..

[24]  Aivar Sootla,et al.  Geometric Properties of Isostables and Basins of Attraction of Monotone Systems , 2017, IEEE Transactions on Automatic Control.