Distributed adaptive fault‐tolerant leader‐following formation control of nonlinear uncertain second‐order multi‐agent systems

This paper presents a distributed integrated fault diagnosis and accommodation scheme for leader‐following formation control of a class of nonlinear uncertain second‐order multi‐agent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The time‐varying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault‐tolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closed‐loop stability and asymptotic convergence properties of the leader‐follower formation are rigorously established under different modes of the fault‐tolerant control system.     

Adhesion and Friction Evaluation of Textured Slider Surfaces in Ultra-Low Flying Head-Disk Interfaces

To achieve extremely high-density magnetic recording of 1Tbit per square inch using conventional technologies, the distance between the recording slider and the rotating disk needs to be less than 5nm. For successful operation, disk and slider surfaces must also be extremely smooth with root-mean-square roughness values of few angstroms. However, ultra-low flying super smooth head-disk interfaces may be exposed to a significant amount of intermittent contact, adhesion, stiction and friction that can cause the interface to collapse. In order to circumvent such problems, many novel techniques have been proposed, such as laser zone texturing, contact pads and surface microtexturing. A reliable method to reduce adhesion and friction in ultra-low flying head-disk interfaces is to control the area of contact and roughen the interface, which allows the slider to fly at sub-5nm with minimal contact. A technique known as preferential texturing provides a unique roughening of the air-bearing surface, where parts of the surface are removed, i.e., subtractive texturing process. In this paper, the effect of preferential texturing (roughening) of slider air-bearing surfaces on the adhesion and friction forces are investigated using quasi-dynamic models. The simulation results show that surface texturing reduces adhesion and friction by reducing the effective area of contact between the slider and media surfaces and by preferentially roughening the interface. The simulation results of friction compare favorably with experimental data.     

Effect of hard-disk drive spindle motor vibration on dynamic microwaviness and flying-height modulation

In order to achieve higher recording densities up to 1 Terabit per square inch using conventional magnetic recording technologies, the recording slider will need to be physically spaced very close to the rotating disk, possibly via the use of an air-bearing surface. However, as the recording slider is flying at such ultra-low spacing of few nanometers over a high-speed rotating disk, it is experiencing disturbances from various different sources and of a wide frequency range. These disturbances may cause the recording slider to vibrate significantly, a condition known as flying-height modulation (FHM), which may result in data loss and possibly head–disk interface failure. A significant source of slider excitation is due to low frequency surface topographical features of the rotating disk, termed dynamic microwaviness. Dynamic microwaviness is a dynamic property of the disk and differs from regular topographical microwaviness, which is a static property. Most research works on dynamic microwaviness and FHM have been focused at the component level, using somewhat idealized conditions, such as high performance air-spindle motors that exhibit very low vibration amplitudes. In this paper, actual hard-disk drive spindle motors are used to investigate the effect of spindle motor vibration on dynamic microwaviness and FHM. It is found that there is a clear connection between spindle motor vibration and dynamic microwaviness that affects FHM.     

Influence of electrolyte co-additives on the performance of dye-sensitized solar cells

The presence of specific chemical additives in the redox electrolyte results in an efficient increase of the photovoltaic performance of dye-sensitized solar cells (DSCs). The most effective additives are 4-tert-butylpyridine (TBP), N-methylbenzimidazole (NMBI) and guanidinium thiocyanate (GuNCS) that are adsorbed onto the photoelectrode/electrolyte interface, thus shifting the semiconductor's conduction band edge and preventing recombination with triiodides. In a comparative work, we investigated in detail the action of TBP and NMBI additives in ionic liquid-based redox electrolytes with varying iodine concentrations, in order to extract the optimum additive/I₂ ratio for each system. Different optimum additive/I₂ ratios were determined for TBP and NMBI, despite the fact that both generally work in a similar way. Further addition of GuNCS in the optimized electrolytic media causes significant synergistic effects, the action of GuNCS being strongly influenced by the nature of the corresponding co-additive. Under the best operation conditions, power conversion efficiencies as high as 8% were obtained.     

A Multiwalled‐Carbon‐Nanotube‐Based Biosensor for Monitoring Microcystin‐LR in Sources of Drinking Water Supplies

A multiwalled carbon nanotube (MWCNT)‐based electrochemical biosensor is developed for monitoring microcystin‐LR (MC‐LR), a toxic cyanobacterial toxin, in sources of drinking water supplies. The biosensor electrodes are fabricated using vertically well‐aligned, dense, millimeter‐long MWCNT arrays with a narrow size distribution, grown on patterned Si substrates by water‐assisted chemical vapor deposition. High temperature thermal treatment (2500 °C) in an Ar atmosphere is used to enhance the crystallinity of the pristine materials, followed by electrochemical functionalization in alkaline solution to produce oxygen‐containing functional groups on the MWCNT surface, thus providing the anchoring sites for linking molecules that allow the immobilization of MC‐LR onto the MWCNT array electrodes. Addition of the monoclonal antibodies specific to MC‐LR in the incubation solutions offers the required sensor specificity for toxin detection. The performance of the MWCNT array biosensor is evaluated using micro‐Raman spectroscopy, including polarized Raman measurements, X‐ray photoelectron spectroscopy, cyclic voltammetry, optical microscopy, and Faradaic electrochemical impedance spectroscopy. A linear dependence of the electron‐transfer resistance on the MC‐LR concentration is observed in the range of 0.05 to 20 μg L^?1, which enables cyanotoxin monitoring well below the World Health Organization (WHO) provisional concentration limit of 1 μg L^?1 for MC‐LR in drinking water.     

Dielectric and thermal studies of segmental dynamics in silica/PDMS and silica/titania/PDMS nanocomposites

Effects of silica and silica/titania nanoparticles on glass transition and segmental dynamics of poly(dimethylsiloxane) (PDMS) were studied for composites of a core–shell type using differential scanning calorimetry, thermally stimulated depolarization current, and dielectric relaxation spectroscopy techniques. Strong interactions between the filler and the polymer suppress crystallinity (T_c, X_c) and affect significantly the evolution of the glass transition in the nanocomposites. The segmental relaxation associated with the glass transition consists of three contributions, arising, in the order of decreasing mobility, from the bulk (unaffected) amorphous polymer fraction (α relaxation), from polymer chains restricted between condensed crystal regions (α_c relaxation), and from the semi‐bound polymers in an interfacial layer with strongly reduced mobility due to interactions with surface hydroxyls of silica and silica/titania nanoparticles (α′ relaxation). The evolution of surface affected CH₃ groups, as well as the degree of interaction of PDMS molecules with surface hydroxyl groups as a function of treatment temperature, was assessed by Fourier transform infrared spectroscopy, thermogravimetry and differential thermal analysis. The effectiveness of silica/PDMS and silica/titania/PDMS nanocomposites as hydrophobic coatings was investigated by static contact angle measurements. It was shown that the presence of titania nanoparticles and adsorbed PDMS promotes the hydrophobic properties of the PDMS coating after treatment in the 80–650°C range. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 41154.     

Distributed fault diagnosis for continuous-time nonlinear systems: The input–output case

In this paper, some new results on distributed fault diagnosis of continuous-time nonlinear systems with partial state measurements are proposed. By exploiting an overlapping decomposition framework, the dynamics of a nonlinear uncertain large-scale dynamical system is described as the interconnections of several subsystems. Each subsystem is monitored by a Local Fault Diagnoser: a set of local estimators, based on the nominal local dynamic model and on an adaptive approximation of the interconnection and of the fault function, allows to derive a local fault decision. A consensus-based protocol is used in order to improve the detectability and the isolability of faults affecting variables shared among different subsystems because of the overlapping decomposition. A sufficient condition ensuring the convergence of the estimation errors is derived. Finally, possibly non-conservative time-varying threshold functions guaranteeing no false-positive alarms and theoretical results dealing with detectability and isolability sufficient conditions are presented.     

Nanostructure,mechanical and tribological properties of reactive magnetron sputtered TiCx coatings

This study describes the correlation between microstructure, mechanical and tribological properties of TiC_x coatings (with x being in the range of 0–1.4), deposited by reactive magnetron sputtering from a Ti target in Ar/C₂H₂ mixtures at ~ 200 °C. The mechanical and tribological properties were found to strongly depend on the chemical composition and the microstructure present. Very dense structures and high hardness, combined with low wear rates and friction coefficients, were observed for coatings with chemical composition close to TiC. X-ray diffraction and X-ray photoelectron spectroscopy analysis, used to evaluate coating microstructure, composition and relative phase fraction, showed that low carbon contents in the coatings lead to sub-stoichiometric nanocrystalline TiC_x coatings being deposited, whilst higher carbon contents gave rise to dual phase nanocomposite coatings consisting of stoichiometric TiC nanocrystallites and free amorphous carbon. Optimum performance was observed for nanocomposite TiC_1.1 coatings, comprised of nanocrystalline nc-TiC (with an average grain size of ~ 15 nm) separated by 2–3 monolayers of an amorphous a-DLC matrix phase.     

Spillover of primary oxides as a dynamic catalytic effect of interactive hypo-d-oxide supports

The aim of the present paper is to introduce electron conductive and d-d-interactive individual and composite hypo-d-oxides of increased altervalent capacity, or their suboxides (Magneli phases), as catalytic supports and therefrom provide: (i) the Strong Metal-Supports Interaction (SMSI) effect and (ii) dynamic spillover interactive transfer of primary oxides (M-OH) for further electrode reactions and thereby advance the overall electrocatalytic activity. Since hypo-d-oxides feature the exchange membrane properties, the higher the altervalent capacity, the higher the spillover effect. This is the reason why anatase titania has now been doped with a certain amount of colloidal tungstenia (WO₃) ingredient, and the latter individually employed as the interactive catalyst support. Potentiodynamic experiments have shown that the reversible peak of the primary oxide growth on Pt, Ru and Au supported upon hypo-d-oxides and suboxides becomes distinctly increased in the charge capacity and shifted to remarkably more negative potential values, so that it starts even within the range of H-adatoms desorption, while its reduction extends until and merge with the UPD of hydrogen atoms. With wet tungstenia-doped titania-supported Pt catalyst in membrane cells, these peaks dramatically increase in their charge capacity and reversibly become shrunk with decreased moisture content in the feeding inert gas mixture, and vice versa. Such distinct potentiodynamic scans in conjunction with some broadened complementary kinetic electrocatalytic improvements, rising from the same hypo-d-oxide and/or suboxide interactive support effects, have been proved to be the best and comparable experimental evidence for the spillover effect of primary oxides.     

Using localizing learning to improve supervised learning algorithms

Slow learning of neural-network function approximators can frequently be attributed to interference, which occurs when learning in one area of the input space causes unlearning in another area. To mitigate the effect of unlearning, this paper develops an algorithm that adjusts the weights of an arbitrary, nonlinearly parameterized network such that the potential for future interference during learning is reduced. This is accomplished by the reduction of a biobjective cost function that combines the approximation error and a term that measures interference. An analysis of the algorithm's convergence properties shows that learning with this algorithm reduces future unlearning. The algorithm can be used either during online learning or can be used to condition a network to have immunity from interference during a future learning stage. A simple example demonstrates how interference manifests itself in a network and how less interference can lead to more efficient learning. Simulations demonstrate how this new learning algorithm speeds up the training in various situations due to the extra cost function term.