PID and state feedback controllers using DNA strand displacement reactions

Nuno Paulino, Mathias Foo, Jongmin Kim, Declan Bates

    Research output: Contribution to journalArticlepeer-review

    39 Citations (Scopus)
    219 Downloads (Pure)

    Abstract

    Nucleic acid-based chemistry is a strong candidate framework for the construction of future synthetic biomolecular control circuits. Previous work has demonstrated the capacity of circuits based on DNA strand displacement (DSD) reactions to implement digital and analogue signal processing in vivo, including in mammalian cells. To date, however, feedback control system designs attempted within this framework have been restricted to extremely simple proportional or proportional-integral controller architectures. In this letter, we significantly extend the potential complexity of such controllers by showing how time-delays, numerical differentiation (to allow PID control), and state feedback may be implemented via chemical reaction network-based designs. Our controllers are implemented and tested using VisualDSD, a rapid-prototyping tool that allows precise analysis of computational devices implemented using nucleic acids, via both deterministic and stochastic simulations of the DSD reactions.

    Original languageEnglish
    Article number8721529
    Pages (from-to)805-810
    Number of pages6
    JournalIEEE Control Systems Letters
    Volume3
    Issue number4
    Early online date24 May 2019
    DOIs
    Publication statusPublished - 1 Oct 2019

    Bibliographical note

    © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    Keywords

    • Biomolecular systems
    • control applications
    • PID control

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Control and Optimization

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