Modelling of signal uncertainty and control objectives in robust controller design

This work develops a new paradigm for optimal robust controller synthesis in the frequency domain. A detailed examination is made of the engineering motivation and engineering efficacy underlying the various strands of robust control theory. The modelling of (a) signal uncertainty and (b) control system objectives in both Tioo and C\ control theories is considered in particular detail. Based on this examination, a theory which can fa irly be described as ‘a m odified 7ioo control theory’ or ‘a frequency domain C\ control theory’ is proposed. New signal sets for the modelling of uncertain signals are introduced. It is argued that these models more faithfully capture the way in which uncertain signals act on real physical systems. It is shown that by adopting these new models for uncertain signals, control theory can be used to non-conservatively minimise maximum tracking errors in the time domain, in the SISO case. In the MIMO case, the problem of optimally synthesising a controller to non-conservatively minimise tracking errors in the time domain leads to a modest variation on existing control theory, requiring the usual norm to be modified slightly. It is argued th a t the proposed paradigm in general achieves a better quality of control and more fa ith fu lly expresses the true objectives of feedback control systems. The proposed development is seen to also extend naturally to Ti.2 control theory, and indeed provides a new deterministic justification for the 7^2 control problem in the MIMO case. The question of design transparency in the synthesis of optimal robust controllers for multivariable systems is considered in detail. The implications of the proposed paradigm for transparency of design and weighting function selection are detailed. A decoupling design procedure for robust controller synthesis is proposed which, under certain restrictive conditions, allows the calculation of super-optimal robust controllers on a loop by loop basis. The usefulness of a classical decoupling approach to MIMO control system design in the context of multivariable robust control theory is demonstrated. A number of design examples are presented which show how the ideas and methods developed in this work can be applied to realistic control problems

Exploiting the dynamic properties of covalent modification cycle for the design of synthetic analog biomolecular circuitry

Background: Cycles of covalent modification are ubiquitous motifs in cellular signalling. Although such signalling cycles are implemented via a highly concise set of chemical reactions, they have been shown to be capable of producing multiple distinct input-output mapping behaviours – ultrasensitive, hyperbolic, signal-transducing and threshold-hyperbolic. Results: In this paper, we show how the set of chemical reactions underlying covalent modification cycles can be exploited for the design of synthetic analog biomolecular circuitry. We show that biomolecular circuits based on the dynamics of covalent modification cycles allow (a) the computation of nonlinear operators using far fewer chemical reactions than purely abstract designs based on chemical reaction network theory, and (b) the design of nonlinear feedback controllers with strong performance and robustness properties. Conclusions: Our designs provide a more efficient route for translation of complex circuits and systems from chemical reactions to DNA strand displacement-based chemistry, thus facilitating their experimental implementation in future Synthetic Biology applications

Restoring circadian gene profiles in clock networks using synthetic feedback control

The circadian system—an organism’s built-in biological clock—is responsible for orchestrating biological processes to adapt to diurnal and seasonal variations. Perturbations to the circadian system (e.g., pathogen attack, sudden environmental change) often result in pathophysiological responses (e.g., jetlag in humans, stunted growth in plants, etc.) In view of this, synthetic biologists are progressively adapting the idea of employing synthetic feedback control circuits to alleviate the effects of perturbations on circadian systems. To facilitate the design of such controllers, suitable models are required. Here, we extend our recently developed model for the plant circadian clock—termed the extended S-System model—to model circadian systems across different kingdoms of life. We then use this modeling strategy to develop a design framework, based on an antithetic integral feedback (AIF) controller, to restore a gene’s circadian profile when it is subject to loss-of-function due to external perturbations. The use of the AIF controller is motivated by its recent successful experimental implementation. Our findings provide circadian biologists with a systematic and general modeling and design approach for implementing synthetic feedback control of circadian systems

On the stability of nucleic acid feedback control systems

Recent work has shown how chemical reaction network theory may be used to design dynamical systems that can be implemented biologically in nucleic acid-based chemistry. While this has allowed the construction of advanced open-loop circuitry based on cascaded DNA strand displacement (DSD) reactions, little progress has so far been made in developing the requisite theoretical machinery to inform the systematic design of feedback controllers in this context. Here, we develop a number of foundational theoretical results on the equilibria, stability, and dynamics of nucleic acid controllers. In particular, we show that the implementation of feedback controllers using DSD reactions introduces additional nonlinear dynamics, even in the case of purely linear designs, e.g. PI controllers. By decomposing the effects of these non-observable nonlinear dynamics, we show that, in general, the stability of the linear system design does not necessarily imply the stability of the underlying chemical reaction network, which can be lost under experimental variability when feedback interconnections are introduced. We provide an in-depth theoretical analysis, and present an example to illustrate when the linear design does not capture the instability of the full nonlinear system implemented as a DSD reaction network, and we further confirm these results using Visual DSD, a bespoke software tool for simulating nucleic acid-based circuits. Our analysis highlights the many interesting and unique characteristics of this important new class of feedback control systems. (C) 2020 Elsevier Ltd. All rights reserved.11Nsciescopu

Management of primary blast lung injury: a comparison of airway pressure release versus low tidal volume ventilation

BackgroundPrimary blast lung injury (PBLI) presents as a syndrome of respiratory distress and haemoptysis resulting from explosive shock wave exposure and is a frequent cause of mortality and morbidity in both military conflicts and terrorist attacks. The optimal mode of mechanical ventilation for managing PBLI is not currently known, and clinical trials in humans are impossible due to the sporadic and violent nature of the disease.MethodsA high-fidelity multi-organ computational simulator of PBLI pathophysiology was configured to replicate data from 14 PBLI casualties from the conflict in Afghanistan. Adaptive and responsive ventilatory protocols implementing low tidal volume (LTV) ventilation and airway pressure release ventilation (APRV) were applied to each simulated patient for 24 h, allowing direct quantitative comparison of their effects on gas exchange, ventilatory parameters, haemodynamics, extravascular lung water and indices of ventilator-induced lung injury.ResultsThe simulated patients responded well to both ventilation strategies. Post 24-h investigation period, the APRV arm had similar PF ratios (137 mmHg vs 157 mmHg), lower sub-injury threshold levels of mechanical power (11.9 J/min vs 20.7 J/min) and lower levels of extravascular lung water (501 ml vs 600 ml) compared to conventional LTV. Driving pressure was higher in the APRV group (11.9 cmH2O vs 8.6 cmH2O), but still significantly less than levels associated with increased mortality.ConclusionsAppropriate use of APRV may offer casualties with PBLI important mortality-related benefits and should be considered for management of this challenging patient group

Mathematical and Computational Modelling in Critical Illness

Mathematical and computational modelling are assuming a prominent role in investigating the complex pathophysiological states and therapeutic strategies in critical illness. This editorial briefly illustrates the models of the respiratory and cardiovascular systems developed in the last decades, and their advantages and disadvantages with respect to traditional methods of research, i.e. trials in humans and animals. The future direction and application of these high-fidelity and highly integrated models will be to facilitate the development of bedside patient-clones to guide the clinical management of critically ill patients

Biomolecular implementation of nonlinear system theoretic operators

Synthesis of biomolecular circuits for controlling molecular-scale processes is an important goal of synthetic biology with a wide range of in vitro and in vivo applications, including biomass maximization, nanoscale drug delivery, and many others. In this paper, we present new results on how abstract chemical reactions can be used to implement commonly used system theoretic operators such as the polynomial functions, rational functions and Hill-type nonlinearity. We first describe how idealised versions of multi-molecular reactions, catalysis, annihilation, and degradation can be combined to implement these operators. We then show how such chemical reactions can be implemented using enzyme-free, entropy-driven DNA reactions. Our results are illustrated through three applications: (1) implementation of a Stan-Sepulchre oscillator, (2) the computation of the ratio of two signals, and (3) a PI+antiwindup controller for regulating the output of a static nonlinear plant