Darlington, APS, Kim, J orcid.org/0000-0002-3456-6614 and Bates, DG (2019) Robustness Analysis of a Synthetic Translational Resource Allocation Controller. IEEE Control Systems Letters, 3 (2). pp. 266-271. ISSN 2475-1456
Abstract
Recent research in Synthetic Biology has highlighted the potential of translational resource allocation controllers to improve circuit modularity by dynamically allocating finite cellular resources in response to fluctuating circuit demands. The design of such controllers is complicated by the significant levels of parametric uncertainty that arise in their biological implementations. Tools from robust control, such as µ-analysis, can be used to determine the robustness of controller designs to parametric uncertainty, but require further development to allow their application to biomolecular control systems, which are typically highly non-linear, and contain multiple uncertainties that cannot be represented using the standard linear fractional transformation formalism. Here, we show how an LFT (Linear Fractional Transformation)-free formulation of the µ-analysis problem can be used to analyse and compare the robustness of alternative potential implementations of a translational resource allocation controller that utilises orthogonal ‘circuit-specific’ ribosomes to translate circuit genes. Our results provide useful guidelines for the construction of robust resource allocation circuitry for multiple future biotechnological applications.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This article is protected by copyright. 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: | synthetic biology; robustness analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Aug 2018 10:42 |
Last Modified: | 13 Dec 2018 13:55 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/LCSYS.2018.2867368 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:134950 |