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Comput Chem Eng. 2017 Apr 06;99:145-157. doi: 10.1016/j.compchemeng.2017.01.027.

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

Computers & chemical engineering

Mathias Foo, Jongrae Kim, Rucha Sawlekar, Declan G Bates

Affiliations

  1. Warwick Integrative Synthetic Biology Centre, School of Engineering, University of Warwick, Coventry CV4 7AL, UK.
  2. School of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.

PMID: 28392606 PMCID: PMC5362158 DOI: 10.1016/j.compchemeng.2017.01.027

Abstract

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

Keywords: Biological engineering; CRN, chemical reaction network; Chemical reaction network theory; DNA, deoxyribonucleic acid; DSD, DNA strand displacement; Enzymatic reaction process; FF, feedforward; IMC, internal model control; LHS, left-hand-side; ODE, ordinary differential equation; PI, proportional-integral; Process control; RHS, right-hand-side; Synthetic biology

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