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In this article, we study adaptation mechanisms in a class of phosphorylation cycles where allosteric binding and gene autoregulation mechanisms regulate the phosphorylation processes. We show that both mechanisms enable a robust setpoint regulation of the regulator metabolite in the presence of constant, as well as periodic, external stimuli. The allosteric binding mechanism without the presence of gene autoregulation can serve as an integral controller. Furthermore, we show that the incorporation of a gene autoregulation mechanism enables the gene expression system to act as a genetic oscillator, which allows for the adaptation mechanism to periodic external stimuli. These results provide a theoretical explanation to the cell homeostasis under quasi-constant environmental conditions, as well as periodic, biological rhythms.

In this work we present a constructive method to design a family of virtual contraction based controllers that solve the standard trajectory tracking problem of flexible-joint robots (FJRs) in the port-Hamiltonian (pH) framework. The proposed design method, called virtual contraction based control (v-CBC), combines the concepts of virtual control systems and contraction analysis. It is shown that under potential energy matching conditions, the closed-loop virtual system is contractive and exponential convergence to a predefined trajectory is guaranteed. Moreover, the closed-loop virtual system exhibits properties such as structure preservation, differential passivity and the existence of (incrementally) passive maps., Comment: 10 pages, 4 figures, journal paper

Recently, 3D porous graphene–polymer composite-based piezoresistive sensors have gained significant traction in the field of flexible electronics owing to their ultralightweight nature, high compressability, robustness, and excellent electromechanical properties. In this work, we present an improved facile recipe for developing repeatable, reliable, and linear 3D graphene–polydimethylsiloxane (PDMS) spongy sensors for internet of things (IoT)-enabled wearable systems and smart consumer products. Fundamental morphological characterization and sensing performance assessment of the piezoresistive 3D graphene–polymer sensor were conducted to establish its suitability for the development of squeezable, flexible, and skin-mountable human motion sensors. The density and porosity of the sponges were determined to be 250 mg cm−3 and 74% respectively. Mechanical compressive loading tests conducted on the sensors revealed an average elastic modulus as low as ∼56.7 kPa. Dynamic compressive force-resistance change response tests conducted on four identical sensors revealed a linear piezoresistive response (in the compressive load range 0.42–2.18 N) with an average force sensitivity of 0.3470 ± 0.0794 N−1. In addition, an accelerated lifetime test comprising 1500 compressive loading cycles (at 3.90 N uniaxial compressive loading) was conducted to demonstrate the long-term reliability and stability of the sensor. To test the applicability of the sensors in smart wearables, four identical graphene–PDMS sponges were configured on the fingertip regions of a soft nitrile glove to develop a pressure sensing smart glove for real-time haptic pressure monitoring. Similarly, the sensors were also integrated into the Philips 9000 series electric shaver to realize smart shaving applications with the ability to monitor shaving motions. Furthermore, the readiness of our system for next-generation IoT-enabled applications was demonstrated by integrating the smart glove with an embedded system software utilizing the an open source microcontroller platform. The system was capable of identifying real-time qualitative pressure distribution across the fingertips while grasping daily life objects, thus establishing the suitability of such sensors for next-generation wearables for prosthetics, consumer devices, and personalized healthcare monitoring devices.

This paper studies static output feedback stabilization of continuous-time (incrementally) passive nonlinear systems where the control actions can only be chosen from a discrete (and possibly finite) set of points. For this purpose, we are working under the assumption that the system under consideration is large-time norm observable and the convex hull of the realizable control actions contains the target constant input (which corresponds to the equilibrium point) in its interior. We propose a nearest-neighbor based static feedback mapping from the output space to the finite set of control actions, that is able to practically stabilize the closed-loop systems. Consequently, we show that for such systems with $m$-dimensional input space, it is sufficient to have $m+1$ discrete input points (other than zero for general passive systems or the target constant input for incrementally passive systems). Furthermore, we present a constructive algorithm to design such $m+1$ nonzero input points that satisfy the conditions for practical stability using our proposed nearest-neighbor control., Comment: 13 pages, double-column, journal submission, revised version

The use of next-generation sequencing technologies in drinking water distribution systems (DWDS) has shed insight into the microbial communities' composition, and interaction in the drinking water microbiome. For the past two decades, various studies have been conducted in which metagenomics data have been collected over extended periods and analyzed spatially and temporally to understand the dynamics of microbial communities in DWDS. In this literature review, we outline the findings which were reported in the literature on what kind of occupancy-abundance patterns are exhibited in the drinking water microbiome, how the drinking water microbiome dynamically evolves spatially and temporally in the distribution networks, how different microbial communities co-exist, and what kind of clusters exist in the drinking water ecosystem. While data analysis in the current literature concerns mainly with confirmatory and exploratory questions pertaining to the use of metagenomics data for the analysis of DWDS microbiome, we present also future perspectives and the potential role of artificial intelligence (AI) and mechanistic models to address the predictive and mechanistic questions. The integration of meta-omics, AI, and mechanistic models transcends metagenomics into functional metagenomics, enabling deterministic understanding and control of DWDS for clean and safe drinking water systems of the future.

In this paper, we tackle the fault-compensation controller in the context of Marko-vian Jump Linear Systems (MJLS). More specifically, we propose the design of H∞ Fault-Compensation Controllers under the MJLS formulation, which is provided in terms of linear matrices inequalities optimization problems. These particular controllers have as the main motivation the network communication loss which is inherent to any automation process. We present a numerical example of a coupled tank system, where a Monte Carlo simulation illustrates the feasibility of the proposed solution. The results show that the proposed approach is indeed a valuable alternative to compensate for the fault occurrence.

In this paper, we propose a new robustness notion that is applicable for certifying systems' safety with respect to external disturbance signals. The proposed input-to-state safety (ISSf) notion allows us to certify systems' safety in the presence of the disturbances which is analogous to the notion of input-to-state stability (ISS) for analyzing systems' stability., 9 pages, pre-print submitted to Automatica

Flow sensors found in animals often feature soft and slender structures (e.g. fish neuromasts, insect hairs, mammalian stereociliary bundles, etc) that bend in response to the slightest flow disturbances in their surroundings and heighten the animal’s vigilance with respect to prey and/or predators. However, fabrication of bioinspired flow sensors that mimic the material properties (e.g. low elastic modulus) and geometries (e.g. high-aspect ratio (HAR) structures) of their biological counterparts remains a challenge. In this work, we develop a facile and low-cost method of fabricating HAR cantilever flow sensors inspired by the mechanotransductory flow sensing principles found in nature. The proposed workflow entails high-resolution 3D printing to fabricate the master mould, replica moulding to create HAR polydimethylsiloxane (PDMS) cantilevers (thickness = 0.5–1 mm, width = 3 mm, aspect ratio = 20) with microfluidic channel (150 μm wide × 90 μm deep) imprints, and finally graphene nanoplatelet ink drop-casting into the microfluidic channels to create a piezoresistive strain gauge near the cantilever’s fixed end. The piezoresistive flow sensors were tested in controlled airflow (0–9 m s−1) inside a wind tunnel where they displayed high sensitivities of up to 5.8 kΩ m s−1, low hysteresis (11% of full-scale deflection), and good repeatability. The sensor output showed a second order dependence on airflow velocity and agreed well with analytical and finite element model predictions. Further, the sensor was also excited inside a water tank using an oscillating dipole where it was able to sense oscillatory flow velocities as low as 16–30 μm s−1 at an excitation frequency of 15 Hz. The methods presented in this work can enable facile and rapid prototyping of flexible HAR structures that can find applications as functional biomimetic flow sensors and/or physical models which can be used to explain biological phenomena.

Using recent results on the incremental stability analysis via contraction and on internal model principle, we revisit the pinning synchronization problem in nonlinear multi-agent systems (MAS). We provide sufficient and necessary conditions for both the pinned agents as well as the rest of the agents to guarantee the state synchronization. For the non-pinned agents, we present a distributed control framework based only on the relative local state measurement and we give sufficient conditions for the contractivity of the individual virtual systems in order to achieve pinning synchronization. Numerical simulation is given to illustrate the main results.

In this letter, we investigate the formation control problem of mobile robots moving in the plane where, instead of assuming robots to be simple points, each robot is assumed to have the form of a disk with equal radius. Based on interior angle measurements of the neighboring robots' disk, which can be obtained from low-cost vision sensors, we propose a gradient-based distributed control law and show the exponential convergence property of the associated error system. By construction, the proposed control law has the appealing property of ensuring collision avoidance between neighboring robots. We also present simulation results for {a team} of four circular mobile robots forming a rectangular shape., 6 pages, submitted to the 59th IEEE Conf. Dec. Control and IEEE Control Systems Letters

We tackle the fault accommodation control (FAC) in the Markovian jump linear system (MJLS) framework for the discrete-time domain, under the assumption that it is not possible to access the Markov chain mode. This premise brings some challenges since the controllers are no longer allowed to depend on the Markov chain, meaning that there is an asynchronism between the system and the controller modes. To tackle this issue, a hidden Markov chain ((Formula presented.), (Formula presented.)) is used where θ(k) denotes the Markov chain mode, and (Formula presented.) denotes the estimated mode. The main novelty of this work is the design of H∞ and H2 FAC under the MJLS framework considering partial observation of the Markov chain. Both designs are obtained via bilinear matrix inequalities optimization problems, which are solved using coordinate descent algorithm. As secondary results, we present simulations using a two-degree of freedom serial flexible joint robot to illustrate the viability of the proposed approach.

International audience; We study the relationship between the global exponential stability of an invariant manifold and the existence of a semi-definite positive Riemannian metric which is contracted by the flow. In particular, we investigate how the following properties are related to each other (in the global case): i). A manifold is globally ‘‘transversally’' exponentially stable; ii). The corresponding variational system (c.f. (8) in Section II) admits the same property; iii). There exists a degenerate Riemannian metric which is contracted by the flow and can be used to construct a Lyapunov function. We show that the transverse contraction rate being larger than the expansion of the shadow on the manifold is a sufficient condition for the existence of such a Lyapunov function. An illustration of these tools is given in the context of global full-order observer design.

Ultra-high vacuum chemical vapor deposition is a thin film deposition process that features excellent film purity, but is sensitive to the processing variations (such as, the precursors and their dispensers, the reactor’s initial condition, etc.). In this paper, we present the design of a ultra-high vacuum chemical vapor deposition reactor with in situ partial pressure atomic absorption spectroscopy measurement that improves reproducibility and observability of such a process. Our main contributions are: (i) a conceptual control systems design of ultra-high vacuum chemical vapor deposition; (ii) atomic absorption spectroscopy based sensor design for the real-time in situ partial pressure measurements; (iii) a flux dynamical model; (iv) experimental reactor design; and (v) experimental validation of model components and the atomic absorption spectroscopy measurement technique. Our results show that the proposed sensor systems are able to provide real-time measurements of the partial pressure inside the reactor and our proposed flux dynamical model agrees with the measured partial pressure. The latter allows us to use it in the design of model-based output feedback control of the partial pressure.

We present the conceptual design and initial development of the Hysteretic Deformable Mirror (HDM). The HDM is a completely new approach to the design and operation of deformable mirrors for wavefront correction in advanced imaging systems. The key technology breakthrough is the application of highly hysteretic piezoelectric material in combination with a simple electrode layout to efficiently define single actuator pixels. The set-and-forget nature of the HDM, which is based on the large remnant deformation of the newly developed piezo material, facilitates the use of time division multiplexing (TDM) to address the single pixels without the need for high update frequencies to avoid pixel drift. This, in combination with the simple electrode layout, paves the way for upscaling to extremely high pixel numbers ($\geq 128\times 128$) and pixel density ($100/mm^2$) deformable mirrors (DMs), which is of great importance for high spatial frequency wavefront correction in some of the most advanced imaging systems in the world.

In this paper, we analyze next generation sequencing (NGS) data of wastewater treatment plant (WWTP) in the North Water facility for revealing the role of 1236 different genera of microorganisms in the aeration basin to the measured process data. Both the time-series data of NGS and process parameters are pre-processed and analyzed using support vector regression technique and is compared with the deep neural network approach. Local sensitivity analysis is performed on the resulting models. Both machine learning analyses show the importance of a subset of genera to the WWTP process and can be used to enrich / to adapt the well-studied activated sludge model (ASM).

International audience; This article addresses output feedback stabilization of continuous-time nonlinear systems by choosing control actions from a finite set. Working under the assumption that the system under consideration is passive and large-time norm observable, we propose a static feedback mapping, from the output space to the finite set of control actions, which is shown to be practically stabilizing if the convex hull of certain control actions (in the chosen finite set) contains the origin in its interior. Consequently, to construct this stabilizing feedback, it suffices to have, in addition to a zero symbol, another m + 1 elements in the control set which form an m-simplex in R m (the input, and output space).

We study the asymptotic stability of Lur'e systems with butterfly hysteresis nonlinearities modeled by the Preisach operators with respect to a set of equilibrium points. We present the input-output rate property of the Preisach operators that exhibit butterfly hysteresis behavior. Based on this characterization, we present sufficient conditions on the linear systems that guarantee the asymptotic stability of the closed-loop system to a set of equilibrium points via circle criterion. Finally numerical simulations are presented to demonstrate these results.

This study presents a revenue maximisation strategy for market integration of a novel wave energy converter (WEC), part of the Ocean Grazer platform. In particular, the authors evaluate and validate the aforementioned revenue maximisation model predictive control (MPC) strategy through extensive simulations and by checking the underlying assumptions of the strategy implementation. Accordingly, an annual simulation of the MPC strategy is shown, which illustrates seasonality effects; furthermore, a benchmark against a heuristic strategy is presented, followed by analyses of the parameter sensitivity and the assumptions on the control loop information that the MPC receives. These efforts shed some light on the impact of variations of the considered parameters and variables on the total revenue and provide insights to optimally scale the WEC. Lastly, the challenges associated with the deployment of such a strategy are addressed, followed by concluding remarks.

We present the modeling and analysis of electrical coupling in a hysteretic deformable mirror with 2D memory piezoac- tuators, which are made of a purposely-designed piezomaterial sandwiched between electrodes arranged crosswise and actuated by a multiplexing approach. Using a modified Miller model to describe the memory effect which is based on the ferroelectric domain switching processes, the proposed framework is used to simulate the electric field dependence of the strain in the piezoelectric material that exhibits asymmetric butterfly loops with remnant deformation through the finite element method. The desired butterfly memory effect in the material is obtained by modifying the saturated dipole polarization curve in the Miller model. The proposed method allows us to numerically investigate the electrical coupling between actuators in more detail and correspondingly understand their influence to the mirror facesheet.

In this work, a numerical model is developed in order to investigate the adaptability of the multi-pump multi-piston power take-off ((MPPTO)-P-2) system of a novel wave energy converter (WEC). This model is realized in the MATLAB/SIMULINK environment, using the multi-body dynamics solver Multibody (TM), which is based on the open-source tool WEC-Sim. Furthermore, the hydrodynamic coefficients are calculated using the open-source code NEMOH. After providing the description of the model, it is validated against experimental results and an analytical model, showing good agreement with both. Subsequently, simulations for a single floater device with a multi-piston pump (MPP) unit using our numerical model are carried out to demonstrate the adaptability of the WEC. In addition, the results demonstrate that the MPP with a simple control strategy can extract more energy than any non adaptable piston pump under various sea states. Finally, a floater blanket (an array of interconnected floaters) model is developed to shed some light on the hydrodynamic response and the performance of MPPs. The developed numerical model will be used in the future to optimize the (MPPTO)-P-2 configuration, and to develop an energy maximization control strategy for the (MPPTO)-P-2 system. (C) 2017 Elsevier Ltd. All rights reserved.

In this paper, we propose a trajectory tracking controller for fully-actuated port-Hamiltonian (pH) mechanical systems, which is based on recent advances in contraction analysis and differential Lyapunov theory. The tracking problem is solved by defining a suitable invariant sliding manifold which provides a desired steady state behavior. The manifold is then made attractive via contraction techniques. Finally, we present numerical simulation results where a SCARA robot is commanded by the proposed tracking control law.

This paper presents a distributed algorithm for controlling the deployment of a team of mobile agents in formations whose shapes can be characterized by a broad class of polygons, including regular ones, where each agent occupies a corner of the polygon. The algorithm shares the appealing properties of the popular distance-based rigid formation control, but with the additional advantage of requiring the control of fewer pairs of neighboring agents. Furthermore, the scale of the polygon can be controlled by only one pair of neighboring agents. We also exploit the exponential stability of the controlled formation in order to steer the formation as a whole with translations and rotations in a prescribed way. We provide both theoretical analysis and illustrative simulations.

We study a containment control problem (CCP) and a shape control problem (SCP) for systems whose initial condition is a random variable with known distribution. The two control problems both require exponential convergence to a desired trajectory, which is complemented by either; i) a required cumulative distribution over a prescribed containment set at a specific transient time for the CCP, or; ii) a maximum distance between an attained and a desired probability density function of the state for the SCP. For the CCP, we obtain solutions for both linear and nonlinear systems by designing the closed-loop such that the initial pdf shrinks or contracts to a desired trajectory. For the SCP, we obtain solutions for linear systems and an admissible desired pdf, by designing the closed-loop such that the evolution of the pdf at the transient time is similar to the target pdf.

We study in this paper an optimal input allocation problem for a class of discrete-event systems with dynamic input sequence (DESDIS). In this case, the input space is defined by a finite sequence whose members will be removed from the sequence in the next event if they are used for the current event control input. Correspondingly, the sequence can be replenished with new members at every discrete-event time. The allocation problem for such systems describes many scheduling and allocation problems in logistics and manufacturing systems and leads to a combinatorial optimization problem. We show that for a linear DESDIS given by a Markov chain and for a particular cost function given by the sum of its state trajectories, the allocation problem is solved by re-ordering the input sequence at any given event time based on the potential contribution of the members in the current sequence to the present state of the system. In particular, the control input can be obtained by the minimization/maximization of the present input sequence only.

This paper presents a nonlinear frequency domain model and uses this to assess the performance of a wave energy converter (WEC) array with a nonlinear power take-off (PTO). In this model, the nonlinear PTO forces are approximated by a truncated Fourier series, while the dynamics of the WEC array are described by a set of linear motion equations in the frequency domain, and the hydrodynamic coefficients are obtained with the boundary element method. A single heave absorber is firstly investigated to establish the accuracy of the new model in capturing the nonlinear behaviour of the pumping system. Subsequently, simulations of a 2D array with 18 WECs and a pillar in the centre (representing the tower of a wind turbine) are carried out to understand wave interference effects. Several optimisation strategies are proposed to improve the overall performance of the WEC array. These results demonstrate a computationally effective method for accounting for nonlinear effects in large WEC arrays. The proposed approach may potentially be applied for developing control algorithms for the adaptability of a 2D array to incoming wave excitation.

In this work we propose a family of trajectory tracking controllers for marine craft in the port-Hamiltonian (pH) framework using virtual differential passivity based control (v-dPBC). Two pH models of marine craft are considered, one in a body frame and another in an inertial frame. The structure and workless forces of pH models are exploited to design two virtual control systems which are related to the original marine craft's pH models. These virtual systems are rendered differentially passive with an imposed steady-state trajectory, both by means of a control scheme. Finally, the original marine craft pH models in closed-loop with above controllers solve the trajectory tracking problem. The performance of the closedloop system is evaluated on numerical simulations., Comment: Submitted to CDC 2018