PID and State Feedback Controllers Using DNA Strand Displacement Reactions

Paulino, Nuno; Foo, Mathias; Kim, Jongmin; Bates, Declan G.

doi:10.1109/lcsys.2019.2918977

Cited by 50 publications

(52 citation statements)

References 20 publications

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“…Instead of using separate CRNs for subtraction and integration, both operations are combined to reduce the number of reactions. The additional dynamics used to compute the error in Paulino et al (2019) are removed, and the contributions of the reference and output to the integral are subtracted in (7c-7d) by crossing the contributions from Y ± to V ∓ . The same reactions apply the control gain k i .…”

Section: Representation With Chemical Reactionsmentioning

confidence: 99%

“…As in the previous example, the CRN representation is further simplified by combining the sum of the feedback contributions and reference with the integration of the first state. In this way, we avoid the additional dynamics of representing the sum with the steady state solution of additional reactions, as proposed in Paulino et al (2019). Accounting for the dual rail representation, the CRN results in eight catalysis and two annihilation reactions, given by…”

Section: Representation With Chemical Reactionsmentioning

confidence: 99%

“…An approach that circumvents this limitation is the so-called dual rail representation of system state variables with pairs of concentrations, as in Seelig et al (2006), where a signal x(t) is represented by the difference between two concentrations x(t) = x + (t) − x − (t), corresponding to two chemical species X + and X − . This dual rail framework provides a representation of negative signals, which are necessary for computing the error in a negative feedback control system, and enables the use of molecular concentrations to design feedback control circuits based on linear operators and frequency or state-space designs, see examples in Oishi and Klavins (2011); Yordanov et al (2014); Chiu et al (2015); Foo et al (2017); Paulino et al (2019).…”

Section: Introductionmentioning

confidence: 99%

“…Note that, by representing the gains and subtractions with individual CRNs, the state feedback scheme in Paulino et al (2019) is already simplified with respect to a classical PID controller, since it combines the gains with the subtraction in the same CRN. Here we reduce the complexity further by combining gain, integration and subtraction in the same chemical reactions.…”

Section: Introductionmentioning

confidence: 99%

“…Here we reduce the complexity further by combining gain, integration and subtraction in the same chemical reactions. This allows us to remove two catalysis, two degradation, and one annihilation reactions in the integral control problem, with respect to the approach in Paulino et al (2019). In the state feedback controller, we remove four catalysis and one annihilation reactions, by combining the subtraction with the integration of the first state, and by selecting a plant that does not need degradation reactions for its representation.…”

Section: Introductionmentioning

confidence: 99%

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Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations

Paulino

Foo

Greef

et al. 2019

Preprint

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Chemical reaction networks based on catalysis, degradation, and annihilation may be used as building blocks to construct a variety of dynamical and feedback control systems in Synthetic Biology. DNA strand-displacement, which is based on DNA hybridisation programmed using Watson-Crick base pairing, is an effective primitive to implement such reactions experimentally. However, experimental construction, validation and scale-up of nucleic acid control systems is still significantly lagging theoretical developments, due to several technical challenges, such as leakage, crosstalk, and toehold sequence design. To help the progress towards experimental implementation, we provide here designs representing two fundamental classes of reference tracking control circuits (integral and state-feedback control), for which the complexity of the chemical reactions required for implementation has been minimised. The supplied 'minimally complex' control circuits should be ideal candidates for first experimental validations of nucleic acid controllers.

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Section: Representation With Chemical Reactionsmentioning

confidence: 99%

Section: Representation With Chemical Reactionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations

Paulino

Foo

Greef

et al. 2019

Preprint

Self Cite

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Molecular Cybernetics: Challenges toward Cellular Chemical Artificial Intelligence

Murata

Toyota

Nomura

et al. 2022

Adv Funct Materials

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Research on so-called "chemical artificial intelligence" (CAI) is an emerging field with the aim of constructing information-processing systems with learning capabilities based on chemical methodologies. This can be regarded as an attempt to reconstruct Cybernetics using molecular based systems. Many chemical reaction systems with computational abilities are proposed, but most are fixed functions that deliver molecular output for a given molecular input. On the other hand, chemical AI is a system with learning capability; namely, the output should be variable and gradually change upon repeated molecular inputs. In this paper, a compartmentalization approach for implementing cellular chemical AI using liposomes is discussed. The existing studies in terms of the methods used for assembling systems consisting of many liposomes with different functions, methods for achieving recursiveness and plasticity in chemical reaction systems, and methods for reconfiguring the network topology by liposome deformation are reviewed. Issues that must be addressed in order to realize chemical AI are also identified.

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Construction of logic circuit with modular molecular switching strategy based on DNA strand displacement

Huang,

Shao,

Guo

et al. 2024

Circuit Theory & Apps

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SummaryAt present, many DNA logic circuits have been successfully constructed. However, advanced complex DNA computing tasks with simple structure, fast response, and modularization still remain a huge challenge. In this paper, molecular switch circuits (MSCs) are constructed based on DNA strand displacement to improve above problems. At first, molecular switch is constructed, which is the basic element for building logic circuits. Next, the functions of AND, OR, Fan‐in, and Fan‐out are realized through switches cascading in series or parallel. Furthermore, switch canvas strategy is explored to obtain the shortest reaction path and highest output concentration for circuits. Finally, a novel strategy of integrating computing module using molecular switches is proposed. Here, we construct a half‐adder, half‐subtractor, and a 9‐bit parity checking circuits to verify its feasibility. Compared with the classical monorail and dual‐track logic circuits, the structure scale is reduced by more than two times, and the DNA strands are decreased by more than four times, which effectively reduces the circuit complexity and raises the reaction speed. The above results show that MSC strategy has a great potential to construct large‐scale DNA circuits and provides a development model for the scalability and modularity of biological computing.

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PID and State Feedback Controllers Using DNA Strand Displacement Reactions

Abstract: This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Cited by 50 publications

References 20 publications

Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations

Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations

Molecular Cybernetics: Challenges toward Cellular Chemical Artificial Intelligence

Construction of logic circuit with modular molecular switching strategy based on DNA strand displacement

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