Search

This paper presents a computational geometry approach for the approximation of full state feedback controllers by static output feedback for a class of 2D parabolic partial differential equations. First, the controller is designed with the assumption that the full infinite dimensional state is available for measurement and then it is approximated by a static output feedback controller which requires only few sensor measurements to be realized. The problem of sensor selection is solved by using computational geometry methods. This is achieved by using the feedback kernel to decompose the spatial domain in cells with the property that the volume of the feedback kernel over each cell is the same and equal to a fraction of the volume of the kernel over the entire spatial domain. A sensor is allocated in each of these cells and the subsequent gain optimization is achieved by minimizing the difference of the full state feedback and the approximate static output feedback, in a variational sense. Extensive numerical studies are included to highlight the various aspects of the proposed tessellation-based controller approximation and sensor selection.

This work proposes an algorithm for the optimal guidance of evacuees in indoor environments. The proposed work examines the path-dependent accumulation of hazardous substances inhaled, such as carbon monoxide, and provides an optimal path that ensures that evacuees can survive to emergency exits by guaranteeing the accumulated inhalation of carbon monoxide is below life-threatening levels. The spatiotemporal variation of the hazardous and toxic field, as described by either Poisson or advection-diffusion partial differential equation, is used to compute the accumulated amount of carbon monoxide inhaled. The accumulated amount is given in terms of the line integral of the hazardous field along the escape paths. The effects of carbon monoxide on evacuee speed are considered. To ensure a path with lower carbon monoxide inhalation levels as well as reduced flight times, level sets are used to generate the set of angles for each path. This is done using a coefficient that changes the direction of motion based on the instantaneous carbon monoxide concentration. This coefficient varies based on the level set with a specific critical level set declared such that it is never crossed. The optimization scheme provides the optimal path among all admissible paths having the smallest value below the tolerance levels of the substance. Simulation studies considering both spatially and spatiotemporally varying functions of carbon monoxide in an indoor environment representing a floor of an office building, are provided to further demonstrate evacuation policies in contaminated indoor environments.

N-acetylglucosamine (GlcNAc) branching of Asn (N)-linked glycans inhibits pro-inflammatory T cell responses and models of autoimmune diseases such as Multiple Sclerosis (MS). Metabolism controls N-glycan branching in T cells by regulating de novo hexosamine pathway biosynthesis of UDP-GlcNAc, the donor substrate for the Golgi branching enzymes. Activated T cells switch metabolism from oxidative phosphorylation to aerobic glycolysis and glutaminolysis. This reduces flux of glucose and glutamine into the hexosamine pathway, thereby inhibiting de novo UDP-GlcNAc synthesis and N-glycan branching. Salvage of GlcNAc into the hexosamine pathway overcomes this metabolic suppression to restore UDP-GlcNAc synthesis and N-glycan branching, thereby promoting anti-inflammatory T regulatory (Treg) over pro-inflammatory T helper (TH) 17 and TH1 differentiation to suppress autoimmunity. However, GlcNAc activity is limited by the lack of a cell surface transporter and requires high doses to enter cells via macropinocytosis. Here we report that GlcNAc-6-acetate is a superior pro-drug form of GlcNAc. Acetylation of amino-sugars improves cell membrane permeability, with subsequent de-acetylation by cytoplasmic esterases allowing salvage into the hexosamine pathway. Per- and bi-acetylation of GlcNAc led to toxicity in T cells, whereas mono-acetylation at only the 6 > 3 position raised N-glycan branching greater than GlcNAc without inducing significant toxicity. GlcNAc-6-acetate inhibited T cell activation/proliferation, TH1/TH17 responses and disease progression in Experimental Autoimmune Encephalomyelitis (EAE), a mouse model of MS. Thus, GlcNAc-6-Acetate may provide an improved therapeutic approach to raise N-glycan branching, inhibit pro-inflammatory T cell responses and treat autoimmune diseases such as MS.

Orbital flight of CubeSats at altitudes between 150 and 250 km has the potential to enable a new class of scientific, commercial, and defense-related missions. A study is presented to demonstrate the feasibility of extending the orbital lifetime of a CubeSat in a 210 km orbit. Propulsion consists of an electrospray thruster operating at a 2 W, 0.175 mN thrust, and an specific impulse (Isp) of 500 s. The mission consists of two phases. In phase 1, the CubeSat is deployed from a 414 km orbit and uses the thruster to deorbit to the target altitude of 210 km. In phase 2, the propulsion system is used to extend the mission lifetime until propellant is fully expended. A control algorithm based on maintaining a target orbital energy is presented that uses an extended Kalman filter to generate estimates of the orbital dynamic state, which are periodically updated by Global Positioning System measurements. For phase 1, the spacecraft requires 25.21 days to descend from 414 to 210 km, corresponding to a ΔV=96.25 m...

The approach presented in this paper provides real-time estimation of a gaseous plume concentration using an unmanned aerial vehicle with sensors. The plume is generated by a moving aerial source and is modeled by the unsteady three-dimensional advection–diffusion equation with ambient winds and eddy diffusivities. The approach couples the unmanned aerial vehicle guidance with the performance of the concentration estimator and is implemented with efficient computational methods for real-time estimation. The unmanned aerial vehicle is modeled as a point-mass fixed-wing aircraft resulting in a sixth-order nonlinear dynamical system. The unmanned aerial vehicle is guided toward the region of maximum state-estimation error via a Lyapunov-redesign method. The estimation scheme provides the desired Cartesian velocities of the unmanned aerial vehicle, and a lower-level controller provides the control signals to the unmanned aerial vehicle. The finite volume discretization of the estimator incorporates a second-o...

We propose an adaptive distributed algorithm for distributed observers of linear time-invariant descriptor systems. In the proposed algorithm, the interconnection gains of the resulting distributed unknown input observers are adjusted adaptively and the adaptation law is obtained by a Lyapunov-redesign approach. The scheme uses adaptive gains for each pairwise difference in the coupling term, which are adjusted in proportion to the pairwise differences of the state estimates. A special case where a single adaptive gain is used in each node to uniformly penalise all pairwise differences of the state estimates in the coupling term is also presented. Stability of the proposed schemes is proved and it is shown to be independent of the graph topology of the network. A numerical example is provided to illustrate the performance of the proposed adaptive distributed unknown input observers algorithm and to compare it with the non-interacting local unknown input observers.

The real-time estimation of a gaseous plume that results from gas released into the atmosphere by a moving aerial source is presented. The approach is utilizing a group of UAVs equipped with gas concentration sensors onboard and the concentration measurements are used in an estimation scheme in the form of a Luenberger observer. The estimator is modeled as the advection-diffusion equation, which is solved numerically in real-time using a finite volume method on a dynamically adapted computational grid. The UAVs maintain a rigid flying formation, with the control signals for the leader being provided by the Lyapunov-redesign method, which couples the UAV dynamics to the performance of the estimator. The follower UAVs provide plant information to the estimator and also compute the spatial gradients necessary for the implementation of the guidance scheme. Numerical examples illustrate the performance of the proposed approach.

This study presents a 3-Unit CubeSat design with commercial-off-the-shelf hardware, Teflon®-fueled micropulsed plasma thrusters, and an attitude determination and control approach. The micropulsed plasma thruster is sized by the impulse bit and pulse frequency required for continuous compensation of expected maximum disturbance torques at altitudes between 400 and 1000 km, as well as to perform stabilization of up to 20 deg/s and slew maneuvers of up to 180 deg. The study involves realistic power constraints anticipated on the 3-Unit CubeSat. Attitude estimation is implemented using the q method for static attitude determination of the quaternion using pairs of the spacecraft–sun and magnetic-field vectors. The quaternion estimate and the gyroscope measurements are used with an extended Kalman filter to obtain the attitude estimates. Proportional–derivative control algorithms use the static attitude estimates in order to calculate the torque required to compensate for the disturbance torques and to achie...

This work considers the synchronization control of networked PDEs that have boundary observation and control. The PDEs are assumed identical, with information exchange dictated by a complete directed graph. Parametric uncertainties entering in the boundary, result in structured perturbation terms that may render the open loop system unstable. Additionally constant disturbance terms entering at the boundary are impeding state regulation. To address these parametric uncertainties, a precompensator is utilized to stabilize each networked PDE. Another component of the controller provides an on-line cancellation of the parametric uncertainties by attempting to cancel them through their adaptive estimate, and to attenuate the effects of boundary disturbances, their adaptive estimates are utilized in the controller. To provide a robustness in the adaptive estimation of the parametric uncertainties and the boundary disturbances, the standard adaptive laws are complemented with a consensus protocol term that penalizes the pairwise disagreement of the adaptive estimates. Finally, to enforce synchronization of all networked PDEs, a synchronization controller is included which utilizes only the outputs of all communicating PDE systems weighted by adaptive synchronization gains. These gains, derived from Lyapunov redesign methods, include a consensus term for added robustness and to enforce convergence. Simulation studies of five networked diffusion PDEs with boundary observation and control are included.

Despite regulatory approval of several immune-based treatments for cancer in the past decade, a number of barriers remain to be addressed in order to fully harness the therapeutic potential of the immune system and provide benefits for patients with cancer. As part of the Cancer Moonshot initiative, the Immuno-Oncology Translational Network (IOTN) was established to accelerate the translation of basic discoveries to improve immunotherapy outcomes across the spectrum of adult cancers and to develop immune-based approaches that prevent cancers before they occur. The IOTN currently consists of 32 academic institutions in the USA. By leveraging cutting-edge preclinical research in immunotherapy and immunoprevention, open data and resource sharing, and fostering highly collaborative team science across the immuno-oncology ecosystem, the IOTN is designed to accelerate the generation of novel mechanism-driven immune-based cancer prevention and therapies, and the development of safe and effective personalized immuno-oncology approaches.

This note revisits the navigation problem for a mobile agent in 3D environments and incorporates the accumulated effects of a hazardous spatial field on the mobile agent motion. Such effects are encountered by human evacuation of indoor environments with carbon monoxide as the hazardous field. The accumulated amount of carbon monoxide inhaled during the flight to escape plays a detrimental role in the ability of an evacuee to escape; if this accumulated amount inhaled exceeds a threshold value the evacuee is incapacitated. Using the accumulated amount, represented by the line integral of the spatial field along the chosen escape trajectory, as an augmented state, the navigation problem is cast as an optimal control problem. The solution to the 3D navigation over hazardous fields, which is applicable to both human evacuees in indoor environments and mobile robots traversing over hazardous environments, is presented and a related problem of minimizing the accumulated amount is also formulated and solved. Simulation results are presented to demonstrate the proposed results.

Hashimoto’s encephalopathy (HE) is a presumed autoimmune disorder associated with anti-thyroid autoantibodies and signs and symptoms of encephalopathy. A sub-type of HE is associated with cerebellar dysfunction and ataxia. Immunosuppressive therapy, particularly corticosteroid treatment, is utilized in the majority of cases. Short-term apheresis has been reported with variable patient responses. Here we report the case of a 72 year-old female with an ∼15 year history of cerebellar type HE that had profound improvement in symptoms after long-term apheresis treatment over an ∼2 year period. Following an induction phase, twice-weekly maintenance apheresis of 1 plasma volume reversed long-standing severe gait ataxia that had required a walker, as well as mild cognitive symptoms. This paralleled reductions in anti-thyroid antibody levels. Holidays from apheresis lasting several weeks and/or reductions in maintenance apheresis frequency to once per-week resulted in re-expression of ataxia and cognitive impairments along with a rise in anti-thyroid antibody levels. An apheresis dose-effect was observed whereby parallel rise and fall in both symptomatology and antibody levels would mirror duration between apheresis intervals. To our knowledge, this is the first report of profound therapeutic benefit and a dose-response relationship to long-term apheresis in cerebellar-type HE. This case suggests that maintenance apheresis be considered in responsive patients, particularly in those with contraindications to medical immunosuppression.

This work considers various optimization aspects for the attitude synchronization of spacecraft formation. Revisiting the synchronization controllers that address unknown parameters via adaptive techniques, this work proposes a modification to the synchronization weights employed to enforce state agreement amongst the networked spacecraft. By augmenting a standard adaptive controller that accounts for unknown parameters, with adaptation of the synchronization weights, one opts to improve spacecraft synchronization. The interconnection strengths of the network nodes, responsible for enforcing synchronization amongst spacecraft, are weighted dynamically in proportion to the disagreement between the spacecraft states. Additionally, when all spacecraft are assumed identical, differing only in their orientation and initial conditions, a modification of the standard adaptive parameter laws allows to reach parameter consensus via a dynamic penalization on the pairwise differences of parameter estimates. The proposed adaptive control architecture which allows for adaptation of both parameter uncertainties and synchronization penalty terms is demonstrated via numerical studies of a four-spacecraft network with limited connectivity. As an alternative to the dynamic adjustment of the synchronization gains, a scheme is proposed to optimally select these gains. By considering the sum of deviation-from-the-mean and rotational kinetic energy as appropriate metrics for synchronization, the numerical studies provide insights into the selection of optimal edge-dependent synchronization gains when the initial conditions are assumed available.

Despite the successful discovery of hundreds of variants for complex human traits using genome-wide association studies, the degree to which genes and environmental risk factors jointly affect disease risk is largely unknown. One obstacle toward this goal is that the computational effort required for testing gene-gene and gene-environment interactions is enormous. As a result, numerous computationally efficient tests were recently proposed. However, the validity of these methods often relies on unrealistic assumptions such as additive main effects, main effects at only one variable, no linkage disequilibrium between the two single-nucleotide polymorphisms (SNPs) in a pair or gene-environment independence. Here, we derive closed-form and consistent estimates for interaction parameters and propose to use Wald tests for testing interactions. The Wald tests are asymptotically equivalent to the likelihood ratio tests (LRTs), largely considered to be the gold standard tests but generally too computationally demanding for genome-wide interaction analysis. Simulation studies show that the proposed Wald tests have very similar performances with the LRTs but are much more computationally efficient. Applying the proposed tests to a genome-wide study of multiple sclerosis, we identify interactions within the major histocompatibility complex region. In this application, we find that (1) focusing on pairs where both SNPs are marginally significant leads to more significant interactions when compared to focusing on pairs where at least one SNP is marginally significant; and (2) parsimonious parameterization of interaction effects might decrease, rather than increase, statistical power.

Summary Understanding the cellular properties controlling neural stem and progenitor cell (NSPC) fate choice will improve their therapeutic potential. The electrophysiological measure whole-cell membrane capacitance reflects fate bias in the neural lineage but the cellular properties underlying membrane capacitance are poorly understood. We tested the hypothesis that cell surface carbohydrates contribute to NSPC membrane capacitance and fate. We found NSPCs differing in fate potential express distinct patterns of glycosylation enzymes. Screening several glycosylation pathways revealed that the one forming highly branched N-glycans differs between neurogenic and astrogenic populations of cells in vitro and in vivo. Enhancing highly branched N-glycans on NSPCs significantly increases membrane capacitance and leads to the generation of more astrocytes at the expense of neurons with no effect on cell size, viability, or proliferation. These data identify the N-glycan branching pathway as a significant regulator of membrane capacitance and fate choice in the neural lineage., Highlights • Biophysical property membrane capacitance reflects fate bias in the neural lineage • N-Glycan branching identifies cells with different fates in vitro and in vivo • N-Glycan branching accounts for capacitance differences reflecting fate • Branching affects fate, leading to more differentiated astrocytes and fewer neurons, Flanagan and colleagues tested glycosylation contributions to a unique, fate-specific electrophysiological property of neural stem cells. They found the N-glycan branching pathway generating highly branched N-glycans associated with astrocyte fate. Enhanced branching shifted the electrophysiological property and fate potential of neural stem cells toward astrocytes, revealing the importance of N-glycan branching to neural stem cell differentiation.

Rapidly proliferating cells switch from oxidative phosphorylation to aerobic glycolysis plus glutaminolysis, markedly increasing glucose and glutamine catabolism. Although Otto Warburg first described aerobic glycolysis in cancer cells >90 years ago, the primary purpose of this metabolic switch remains controversial. The hexosamine biosynthetic pathway requires glucose and glutamine for de novo synthesis of UDP-GlcNAc, a sugar-nucleotide that inhibits receptor endocytosis and signaling by promoting N-acetylglucosamine branching of Asn (N)-linked glycans. Here, we report that aerobic glycolysis and glutaminolysis co-operatively reduce UDP-GlcNAc biosynthesis and N-glycan branching in mouse T cell blasts by starving the hexosamine pathway of glucose and glutamine. This drives growth and pro-inflammatory TH17 over anti-inflammatory-induced T regulatory (iTreg) differentiation, the latter by promoting endocytic loss of IL-2 receptor-α (CD25). Thus, a primary function of aerobic glycolysis and glutaminolysis is to co-operatively limit metabolite supply to N-glycan biosynthesis, an activity with widespread implications for autoimmunity and cancer. DOI: http://dx.doi.org/10.7554/eLife.21330.001

Thymocytes are positively selected upon recognition of self peptide–MHC complexes. Demetriou and colleagues show that N-glycosylation of TCR and coreceptor molecules increases the number of CD4+CD8+ thymocytes that are positively selected.

T HIS Note is concerned with the time adaptation of the synchronization gains used in the attitude synchronization control problem. The problem under consideration assumes that a network of N spacecraft can exchange information through an appropriate communication topology and the objective is to synchronize the spacecraft via the appropriate choice of the control inputs so that each spacecraft has identical orientation. This synchronization objective is quantified via the pairwise difference of the orientation states, chosen here as the modified Rodrigues parameters [1,2]. The contribution in this Note follows earlier work [3,4], but with the difference that it does not parameterize the plant parameters and does not attempt to use adaptation of the parameters to design the control laws. Instead, the synchronization gains, used for synchronization penalty, are adapted. The idea behind this time adaptation of the synchronization gains is that the gains used to penalize the pairwise mismatch of the orientation states among the spacecraft should be proportional to the difference between them. This idea of using adaptive adjustment of the synchronization gains was first examined in [5–9] for general finite dimensional systems and in [10] for a class of infinite dimensional systems. In essence, one adjusts the strengths of the interconnections among network nodes in accordancewith adaptive policies. These strengths are represented by the nonzero elements of the time-varyingLaplacianmatrix associated with the networked systems [5]. Before considering the adaptation of the synchronization gains, we revisit the case of constant synchronization gains to explore the optimization of appropriate performance metrics that produce optimal constant synchronization gains. We consider two cases in which the local weights (synchronization gains) of the synchronization signalmay differ for each spacecraft (termed the node-dependent gains or vertex-dependent gains) ormay differ for each of its communicating neighbors (termed the edge-dependent gains). In essence, the third case, serving as the default case, is the one considered in earlier work [3]. The control design and stability for both cases of these constant synchronization gains are examined and an algorithm for obtaining these gains in proportion to the initial pairwise difference of spacecraft states is presented. Additionally, it is shown that the node-independent case (default case) and the node-dependent gains case are special cases to the more general edge-dependent synchronization gain case presented here. The simple optimization of these synchronization gains aims at reducing the transients of the rotational kinetic energy while at the same time trying to improve synchronization. For the latter, an appropriate measure of spacecraft attitude agreement, termed the deviation from themean, is used as the metric for examining success of synchronization. The adaptive adjustment of the synchronization gains leads to combined control and adaptation laws and their stability and convergence properties must be examined. The specifics of the proposed adaptive modification assume that the synchronization signal contains a fixed synchronization gain but the torque inputs for each spacecraft areweighted by a local adaptive synchronization gain. The requisite adaptation laws for the synchronization signals are extracted using Lyapunov redesign methods. The problem formulation along with a summary of established results on attitude dynamics, attitude synchronization, and graph theory are presented in Sec. II. The proposed modifications to the attitude synchronization problem that include constant edgedependent gains is presented in Sec. III, and some guidelines for the selection of the edge-dependent gains satisfying some optimality criteria are summarized in Sec. IV. The main result on the use of adaptive edge-dependent synchronization gains in the control torques is presented in Sec. V, and numerical studies that provide further insight on both the optimality and the adaptation of the synchronization gains are given in Sec. VI. Conclusions with future work follow in Sec. VII.

In a recent study on multiple sclerosis (MS), we observed additive effects and epistatic interactions between variants of four genes that converge to induce T-cell hyperactivity by altering Asn-(N)-linked protein glycosylation: namely, the Golgi enzyme MGAT1, cytotoxic T-lymphocyte antigen 4 (CTLA-4), interleukin-2 receptor-α (IL2RA) and interleukin-7 receptor-α (IL7RA). As the CTLA-4, IL2RA and IL7RA variants are associated with type 1 diabetes (T1D), we examined for joint effects in T1D. Employing a novel conditional logistic regression for family-based data sets, epistatic and additive effects were observed using 1423 multiplex families from the Type 1 Diabetes Genetic Consortium data set. The IL2RA and IL7RA variants had univariate association in MS and T1D, whereas the MGAT1 and CTLA-4 variants associated with only MS or T1D, respectively. However, similar to MS, the MGAT1 variant haplotype interacted with CTLA4 (P=0.03), and a combination of IL2RA and IL7RA (P=0.01). The joint effects of MGAT1, CTLA4, IL2RA, IL7RA and the two interactions using a multiple conditional logistic regression were statistically highly significant (P

Neural stem and progenitor cells (NSPCs) are heterogeneous populations of self-renewing stem cells and more committed progenitors that differentiate into neurons, astrocytes, and oligodendrocytes. Accurately identifying and characterizing the different progenitor cells in this lineage has continued to be a challenge for the field. We found previously that populations of NSPCs with more neurogenic progenitors (NPs) can be distinguished from those with more astrogenic progenitors (APs) by their inherent biophysical properties, specifically the electrophysiological property of whole cell membrane capacitance, which we characterized with dielectrophoresis (DEP). Here, we hypothesize that inherent electrophysiological properties are sufficient to define NPs and APs and test this by determining whether isolation of cells solely by these properties specifically separates NPs and APs. We found NPs and APs are enriched in distinct fractions after separation by electrophysiological properties using DEP. A single round of DEP isolation provided greater NP enrichment than sorting with PSA-NCAM, which is considered an NP marker. Additionally, cell surface N-linked glycosylation was found to significantly affect cell fate-specific electrophysiological properties, providing a molecular basis for the cell membrane characteristics. Inherent plasma membrane biophysical properties are thus sufficient to define progenitor cells of differing fate potential in the neural lineage, can be used to specifically isolate these cells, and are linked to patterns of glycosylation on the cell surface. Stem Cells 2014;32:706–716

The modeling and control of tethered undersea kites for power generation are discussed in this paper. In the first part, we apply the added mass model to underwater kite systems. In the second part, the stability of undersea kite systems is analyzed using two frameworks. The dissipative property of the hydrodynamic force is provided first. Based on this property, the input to state stability of the undersea kite dynamics is established. Moreover, based on the input to state stability, the ultimate boundedness of constrained undersea kite dynamics is also discussed. Finally, an input–output system is proposed, and a passivity-based control signal is designed. The proposed control signal is tested in a baseline simulation, which yields consecutive figure eight cycles with positive net power generation.

Deficiency of the Golgi N-glycan branching enzyme Mgat5 in mice promotes T cell hyperactivity, endocytosis of CTLA-4 and autoimmunity, including a spontaneous multiple sclerosis (MS)-like disease. Multiple genetic and environmental MS risk factors lower N-glycan branching in T cells. These include variants in interleukin-2 receptor-α (IL2RA), interleukin-7 receptor-α (IL7RA), and MGAT1, a Golgi branching enzyme upstream of MGAT5, as well as vitamin D3 deficiency and Golgi substrate metabolism. Here we describe linked intronic variants of MGAT5 that are associated with reduced N-glycan branching, CTLA-4 surface expression and MS (p=5.79×10-9, n=7,741), the latter additive with the MGAT1, IL2RA and IL7RA MS risk variants (p=1.76×10-9, OR=0.67-1.83, n=3,518). © 2013 Elsevier B.V.

In this work, we examine the synchronization control for a class of second order distributed parameter systems. The objective is to design controllers that guarantee agreement between the position and velocity states of N identical second order systems. The controller structure involves coupling terms consisting of the pairwise difference of both position and velocity states of the second order systems in order to enforce consensus. Possible improvements of the agreement amongst the states of each of the systems are considered and compared to the case of noninteracting controllers. Extensions to synchronizing controllers for the case of partial connectivity are discussed. Extensive numerical studies are included to provide a further insight on the effects of synchronization control of second order distributed parameter systems.

This paper presents a model based approach for the real-time estimation of a gaseous plume using a time-varying formation of unmanned aerial vehicles (UAVs). Such a dynamic formation is necessitated by sensor technology limitations that can only obtain concentration measurements and not spatial gradients of concentration. It is assumed that gas is released in the atmosphere by a stationary or a moving aerial source. Each UAV in the flying formation has a single concentration sensor onboard. The estimation scheme, which uses the concentration measurements provided by the UAVs, is built in the form of a Luenberger observer. The plume is reconstructed by solving numerically, and in real-time, the advection-diffusion equation using the finite volume method on a dynamically adapted computational grid. A leader-follower approach is used for the control scheme of the formation flight in order to provide approximations of the spatial gradients. The control signals for the leader, which are provided by the Lyapunov-redesign method, incorporate the concentration gradient measurements. The latter is approximated by simultaneous concentration measurements from the followers. The follower-UAVs keep physics-based prescribed distances from the leader, which are dictated by the performance of the estimator and must follow the estimated length scale for meaningful approximation of spatial gradients of the plume concentration. The numerical simulation results demonstrate the performance of the proposed approach.

This work is concerned with the design of adaptive learning controllers for rendezvous maneuvers of two spacecraft. Unlike earlier efforts using linearized dynamics, the current work considers the nonlinear equations of relative motion. The main idea behind the Lyapunov-based controller design is to allow a flexibility in the time-varying gains to adapt in proportion to the relative distance of the two spacecraft. By augmenting an adaptive controller, one opts to improve controller performance. The adaptation schemes of the controller gains are derived via Lyapunov redesign methods. In order to gain some insights on the choice of the optimal gains, a scheme that penalizes a combination of the relative position error and of the relative velocity error is considered. Extensive numerical studies are provided to further support the theoretical predictions on the choice of controller gains.

An existing attitude tracking control method developed for a FlyGen airborne wind energy (AWE) system is extended to control a GroundGen AWE system. The GroundGen system produces energy through kite-generated aerodynamic forces that tension a flexible tether attached between the kite center of gravity and a ground generator system. The kite is modelled using a six degree of freedom aircraft dynamics model. We first provide an extension of a previously developed attitude tracking theorem which shows the possibility of simultaneously tracking both the effective angle of attack and sideslip angle on the kite. A detailed aerodynamic model with empirical airfoil data and three dimensional wing tip effects is included. A feedback linearization controller is designed, and a baseline simulation is studied for confirming the tracking behavior.

Control of kite trajectories for a tethered undersea kite (TUSK) energy system is studied. A TUSK system consists of a rigid undersea wing (or kite) attached by a tether to a buoy on the ocean surface. A turbine is mounted on the undersea kite to harness hydrokinetic energy from an ocean current when the kite moves in high-speed, cross-current motions. We adopt a six degree of freedom aircraft model that incorporates the translational motion of the kite center of gravity and rotational dynamics of the Euler angles. We assume TUSK system is connected to the fixed surface buoy with a straight-line inelastic tether and harnesses energy in a uniform current. Improved models are developed for added mass effects and hydrodynamic moments due to buoyancy on the underwater kite. We apply a passivity based controller, which has been previously developed for airborne wind energy (AWE) systems, to control the underwater kite trajectory and orientation. A baseline simulation for typical design parameters values in a TUSK system is studied.

Essential biological systems employ self-correcting mechanisms to maintain cellular homeostasis. Mammalian cell function is dynamically regulated by the interaction of cell surface galectins with branched N-glycans. Here we report that N-glycan branching deficiency triggers the Golgi to generate bioequivalent N-glycans that preserve galectin-glycoprotein interactions and cellular homeostasis. Galectins bind N-acetyllactosamine (LacNAc) units within N-glycans initiated from UDP-GlcNAc by the medial-Golgi branching enzymes as well as the trans-Golgi poly-LacNAc extension enzyme β1,3-N-acetylglucosaminyltransferase (B3GNT). Marginally reducing LacNAc content by limiting N-glycans to three branches results in T-cell hyperactivity and autoimmunity; yet further restricting branching does not produce a more hyperactive state. Rather, new poly-LacNAc extension by B3GNT maintains galectin binding and immune homeostasis. Poly-LacNAc extension is triggered by redistribution of unused UDP-GlcNAc from the medial to trans-Golgi via inter-cisternal tubules. These data demonstrate the functional equivalency of structurally dissimilar N-glycans and suggest a self-correcting feature of the Golgi that sustains cellular homeostasis. DOI: http://dx.doi.org/10.7554/eLife.14814.001, eLife digest Most proteins that are released from cells are modified with sugar molecules that allow the proteins to carry out their role properly. These modifications are called glycans, and are made from sugar subunits joined into chains or branched structures. Investigating how the structure of glycans is linked to their role is complicated by the fact that many different glycans exist, made up of different sugars and arranged into different structures. Enzymes located in cell compartments known as the endoplasmic reticulum and the Golgi help to build the glycans. For example, the MGAT family of enzymes found in the Golgi generates branched glycans made up of sugar subunits called N-acetyllactosamine (LacNAc). These glycans form part of a molecular mesh on the surface of cells that controls how certain proteins embedded in the cell membrane behave. This is particularly important in immune cells: reducing the number of branches in the glycans weakens the mesh and causes the cells and their membrane proteins to behave inappropriately. Mkhikian et al. have studied mice that lack specific MGAT enzymes, and so produce LacNAc glycans with drastically fewer branches than normal. Immune cells in these mice had glycans on their surface formed of LacNAc arranged in chains, rather than in short branched structures. These chains turned out to be biologically equivalent to branched LacNAc glycans, containing the same sugar subunits and allowing the immune cells to behave as normal. This suggests that the composition of glycans, rather than their structure, primarily determines their role. Mkhikian et al. also found that the organization of the enzymes inside the Golgi is likely to be responsible for producing these equivalent glycans. A glycan is built up as it passes through the Golgi, with the branching enzymes located earlier in the Golgi than the extending enzymes. Therefore, if the branching enzymes fail to add LacNAc subunits to the glycan, the extending enzymes can step in later to add the missing components. Overall, the results presented by Mkhikian et al. indicate that the large number of structurally diverse glycans may be reduced to a much smaller number of glycans with similar roles, based on subunit composition. This will simplify future studies on LacNAc glycans, and further work could focus on defining which other glycan structures share similar roles. DOI: http://dx.doi.org/10.7554/eLife.14814.002

The waiting time to form a crystal in a unit volume of homogeneous undercooled liquid exhibits a pronounced minimum τX* at a ‘nose temperature' T* located between the glass transition temperature Tg, and the crystal melting temperature, TL. Turnbull argued that τX* should increase rapidly with the dimensionless ratio trg=Tg/TL. Angell introduced a dimensionless ‘fragility parameter', m, to characterize the fall of atomic mobility with temperature above Tg. Both trg and m are widely thought to play a significant role in determining τX*. Here we survey and assess reported data for TL, Tg, trg, m and τX* for a broad range of metallic glasses with widely varying τX*. By analysing this database, we derive a simple empirical expression for τX*(trg, m) that depends exponentially on trg and m, and two fitting parameters. A statistical analysis shows that knowledge of trg and m alone is therefore sufficient to predict τX* within estimated experimental errors. Surprisingly, the liquid/crystal interfacial free energy does not appear in this expression for τX*., The crystal formation waiting time of a homogeneous supercooled liquid exhibits a pronounced minimum depending on temperature, and this minimum is a measure of glass forming ability. Here, the authors propose an expression for this minimum for all metallic glasses that depends only on two fitting parameters.

T cell activation and self-tolerance are tightly regulated to provide effective host defense against foreign pathogens while deflecting inappropriate autoimmune responses. Golgi Asn (N)-linked protein glycosylation coregulates homeostatic set points for T cell growth, differentiation, and self-tolerance to influence risk of autoimmune disorders such as multiple sclerosis (MS). Human autoimmunity is a complex trait that develops from intricate and poorly understood interactions between an individual's genetics and their environmental exposures. Recent evidence from our group suggests that in MS, additive and/or epistatic interactions between multiple genetic and environmental risk factors combine to dysregulate a common biochemical pathway, namely Golgi N-glycosylation. Here, we review the multiple regulatory mechanisms controlling N-glycan branching in T cells and autoimmunity, focusing on recent data implicating a critical role for interleukin-2 (IL-2) and IL-7 signaling.

SUMMARY This paper proposes a new nonlinear detection observer for the detection of component faults and their subsequent accommodation for a class of nonlinear distributed processes. Specifically, the proposed results constitute a significant extension to previous precursory work that utilized a linear observer for both detection and diagnosis of component faults for the same class of nonlinear distributed processes. An added feature of the proposed nonlinear observer under consideration is not simply the inclusion of nonlinear dynamics terms in the detection and diagnostic observers but the inclusion of such additional information in the expression for the dynamic residual threshold. The resulting improved version of a dynamic threshold contributes to the robustness of the detection scheme and minimizes the fault detection time. Two different dynamic threshold approaches are employed within the same nonlinear detection observer leading to improved detection time. A combination of the two thresholds is also considered to arrive at a detection observer that reaps the beneficial attributes of each of the thresholds, thus resulting in significant reduction of the fault detection time. Finally, an adaptive diagnostic observer is proposed that is subsequently utilized in an automated control reconfiguration scheme that accommodates the component faults. Copyright © 2011 John Wiley & Sons, Ltd.

T cell receptor (TCR) signaling enhances β1,6GlcNAc-branching in N-glycans, a phenotype that promotes growth arrest and inhibits autoimmunity by increasing surface retention of cytotoxic T lymphocyte antigen-4 (CTLA-4) via interactions with galectins. N-Acetylglucosaminyltransferase V (MGAT5) mediates β1,6GlcNAc-branching by transferring N-acetylglucosamine (GlcNAc) from UDP-GlcNAc to N-glycan substrates produced by the sequential action of Golgi b1,2-mannosidase I (MIa,b,c), MGAT1, α1,2-mannosidase II (MII, IIx), and MGAT2. Here we report that TCR signaling enhances mRNA levels of MIa,b,c and MII,IIx in parallel with MGAT5, whereas limiting levels of MGAT1 and MGAT2. Blocking the increase in MI or MII enzyme activity induced by TCR signaling with deoxymannojirimycin or swainsonine, respectively, limits β1,6GlcNAc-branching, suggesting that enhanced MI and MII activity are both required for this phenotype. MGAT1 and MGAT2 have an ∼250- and ∼20-fold higher affinity for UDP-GlcNAc than MGAT5, respectively, and increasing MGAT1 expression paradoxically inhibits β1,6GlcNAc branching by limiting UDP-GlcNAc supply to MGAT5, suggesting that restricted changes in MGAT1 and MGAT2 mRNA levels in TCR-stimulated cells serves to enhance availability of UDP-GlcNAc to MGAT5. Together, these data suggest that TCR signaling differentially regulates multiple N-glycan-processing enzymes at the mRNA level to cooperatively promote β1,6GlcNAc branching, and by extension, CTLA-4 surface expression, T cell growth arrest, and self-tolerance. © 2009 by The American Society for Biochemistry and Molecular Biology, Inc.

A theoretical framework of the model reference adaptive control design, adaptive parameter identification and automated fault detection is developed for a class of positive real infinite dimensional systems. Uncertain terms are treated as additive perturbations of the plant operator and the framework provides a unified treatment for model reference control, parameter estimation and fault detection and accommodation. For each design problem the well-posedness and stability of the proposed adaptive scheme are investigated. Extensions to the variable structure observer, to specific forms of the structured perturbation terms and to slowly time-varying systems are also considered within the proposed framework. Such results are summarized as they capitalize on the proposed well-posedness and stability results for the general cases. Copyright © 2008 John Wiley & Sons, Ltd.

This article examines the collocated H∞ control of vector second-order structural systems using an analytical upper-bound method. The structural system considered in this work is that of a cantilevered aluminum beam with a collocated pair of piezoceramic patches to serve as actuators and sensors. An explicit expression that bounds the H∞ norm of collocated structural systems is applied for analysis and control synthesis, resulting in significant computational advantages compared to standard H ∞ analysis and control methods. The proposed approximation method is used to design a static output feedback controller that guarantees a closed-loop H∞ norm less than any user-defined value. This method is validated using a finite element representation of the beam, and then verified experimentally.

A study is presented detailing the simulation of a drag-free follow-up mission to NASA’s Gravity Recovery and Climate Experiment. This work evaluates controller performance, as well as thrust, power, and propellant mass requirements for drag-free spacecraft operation at orbital altitudes of 160–225 km. In addition, sensitivities to thermospheric wind, Global Positioning System signal accuracy, and availability of ephemeris data are studied. Thruster (control actuator) models are based on two different Hall thrusters for providing the orbital along-track acceleration, colloid thrusters for the normal acceleration, and a miniature xenon ion thruster for the cross-track acceleration. At an altitude of 160 km, the maximum along-track thrust component is calculated to be 98 mNwith a required dynamic (throttling) response of 42 mN=s. Themaximum position error at this altitude was shown to be in the along-track direction with a magnitude of 3314.9 nm. At 225 km, the maximum along-track thrust component reduces to 10.3 mN. The maximum dynamic response at this altitude is 4:0 mN=s. For the spacecraft point design considered with a propellant mass fraction of 0.18, the mission lifetime for the 160 km case was calculated to be 0.76 years. This increases 2.27 years at an altitude of 225 km.

A class of nonlinear distributed processes with component and actuator faults is presented. An adaptive detection observer with a time varying threshold is proposed that provides additional robustness with respect to false declarations of faults and minimizes the fault detection time. Additionally, an adaptive diagnostic observer is proposed that is subsequently utilized in an automated control reconfiguration scheme that accommodates the component and actuator faults. An integrated optimal actuator location and fault accommodation scheme is provided in which the actuator locations are chosen in order to provide additional robustness with respect to actuator and component faults. Simulation studies of the Kuramoto-Sivashinsky nonlinear partial differential equation are included to demonstrate the proposed fault detection and accommodation scheme. © 2008 American Institute of Chemical Engineers AIChE J, 2008