Improving the consensus performance via predictive mechanisms

Considering some predictive mechanisms, we show that ultrafast average-consensus can be achieved in networks of interconnected agents. More specifically, by predicting the dynamics of the network several steps ahead and using this information in the design of the consensus protocol of each agent, drastic improvements can be achieved in terms of the speed of consensus convergence, without changing the topology of the network. Moreover, using these predictive mechanisms, the range of sampling periods leading to consensus convergence is greatly expanded compared with the routine consensus protocol. This study provides a mathematical basis for the idea that some predictive mechanisms exist in widely-spread biological swarms, flocks, and networks. From the industrial engineering point of view, inclusion of an efficient predictive mechanism allows for a significant increase in the speed of consensus convergence and also a reduction of the communication energy required to achieve a predefined consensus performance.

ANALYSIS OF PLANAR MECHANISMS BY COMPUTER SUBROUTINE.

A suite of computer subroutines is described which allows rapid analysis of most types of planar mechanism by the writing of a simple computer programme. The analytical techniques of these subroutines are explained, and a worked example is presented to illustrate the use of the package, and to demonstrate its advantages in the calculation of inertia forces within a mechanism.

DISCUSSION OF MECHANISMS OF ACCELERATED AND RETARDED FATIGUE CRACK GROWTH.

The relevance of the effective stress intensity range to crack growth is considered for constant and for variable amplitude loading. The accelerated and retarded growth associated with simple programmed loadings is reported for two steels and an aluminium alloy. The load interaction effects are due to several competing mechanisms, and not due to the single, popular mechanism of crack closure.

MECHANISMS OF ABRASIVE WEAR IN A BORONIZED ALLOY STEEL.

This paper describes the effects of abrasive hardness and size on the 2-body abrasive wear mechanisms of a boronized low alloy steel. It is found that the wear resistance of the boronized steel is much greater against alumina abrasive than against silicon carbide. This difference in wear resistance is much enhanced when the particle size or the applied load is increased. Scanning electron microscopy of the worn specimens and of the used abrasive papers revealed that the enhanced difference in wear resistance between coarse alumina and silicon carbide papers is due to a change in the wear mechanism produced by silicon carbide papers with increasing abrasive particle size.

Mechanisms of erosion of unfilled elastomers by solid particle impact

The mechanisms of material removal were studied during the erosion of two unfilled elastomers (natural rubber and epoxidised natural rubber). The effects of impact velocity and of lubrication by silicone oil were investigated. The development of surface features due to single impacts and during the early stages of erosion was followed by scanning electron microscopy. The basic material removal mechanism at impact angles of both 30° and 90° involves the formation and growth of fine fatigue cracks under the tensile surface stresses caused by impact. No damage was observed after single impacts; it was found that many successive impacts are necessary for material removal. It was found that the erosion rate has a very strong dependance on impact velocity above about 50 ms-1.

Failure mechanisms and toughness of Al2O3 ductile-particle toughened ceramics and SiC fibre-ceramic composites

The development of high performance ceramics and ceramic composites often relies on assumptions about their behaviour during loading and at failure. A crucial influence on the mechanical properties of these materials is the degree of sub-critical cracking, which post mortem investigations cannot adequately reveal. Hence a clear picture of the dynamic micromechanisms of cracking is required if applications of fracture and damage mechanics to theoretical models is to be meaningful.

Analysis of the mechanisms for impaired high-temperature, high-speed performance of 1.3 μm InGaAsP lasers

In this paper, the static and dynamic performance of multi quantum-well (MQW) 1.3 μm InGaAsP Fabry Perot lasers is assessed experimentally and theoretically to identify the mechanisms responsible for impaired high speed performance at elevated temperature. Initially, threshold currents and spontaneous emission spectra are characterized for a range of temperatures from room temperature to 85 °C to indicate a significant increase in non-radiative current contributions. Preliminary estimates are made for the contributions of leakage and Auger recombination rates, found from the dependence of integrated spontaneous emission with carrier density. Drift-diffusion modelling is found to accurately predict the trend of threshold currents over temperature. Using gain modelling good agreement is found between the measured and predicted integrated spontaneous emission intensity. Gain measurements at 85 °C indicate a reduction in RIN frequency to 63% of the 25 °C value which matches well with experimental small signal performance.

The use of C-V techniques to investigate instability mechanisms in M-I-S structures

In the field of flat panel displays, the current leading technology is the Active Matrix liquid Crystal Display; this uses a-Si:H based thin film transistors (TFTs) as the switching element in each pixel. However, under gate bias a-Si:H TFTs suffer from instability, as is evidenced by a shift in the gate threshold voltage. The shift in the gate threshold voltage is generally measured from the gate transfer characteristics, after subjecting the TFT to prolonged gate bias. However, a major drawback of this measurement method is that it cannot distinguish whether the shift is caused by the change in the midgap states in the a-Si:H channel or by charge trapping in the gate insulator. In view of this, we have developed a capacitance-voltage (C-V) method to measure the shift in threshold voltage. We employ Metal-Insulator-Semiconductor (MIS) structures to investigate the threshold voltage shift as they are simpler to fabricate than TFTs. We have investigated a large of number Metal/a-Si:H/Si3N4/Si+n structures using our C-V technique. From, the C-V data for the MIS structures, we have found that the relationship between the thermal energy and threshold voltage shift is similar to that reported by Wehrspohn et. al in a-Si:H TFTs (J Appl. Phys, 144, 87, 2000). The a-Si:H and Si3N4 layers were grown using the radio-frequency plasma-enhanced chemical vapour deposition technique.

Different mechanisms involved in adaptation to stable and unstable dynamics.

Recently, we demonstrated that humans can learn to make accurate movements in an unstable environment by controlling magnitude, shape, and orientation of the endpoint impedance. Although previous studies of human motor learning suggest that the brain acquires an inverse dynamics model of the novel environment, it is not known whether this control mechanism is operative in unstable environments. We compared learning of multijoint arm movements in a "velocity-dependent force field" (VF), which interacted with the arm in a stable manner, and learning in a "divergent force field" (DF), where the interaction was unstable. The characteristics of error evolution were markedly different in the 2 fields. The direction of trajectory error in the DF alternated to the left and right during the early stage of learning; that is, signed error was inconsistent from movement to movement and could not have guided learning of an inverse dynamics model. This contrasted sharply with trajectory error in the VF, which was initially biased and decayed in a manner that was consistent with rapid feedback error learning. EMG recorded before and after learning in the DF and VF are also consistent with different learning and control mechanisms for adapting to stable and unstable dynamics, that is, inverse dynamics model formation and impedance control. We also investigated adaptation to a rotated DF to examine the interplay between inverse dynamics model formation and impedance control. Our results suggest that an inverse dynamics model can function in parallel with an impedance controller to compensate for consistent perturbing force in unstable environments.

Single trial learning of external dynamics: What can the brain teach us about learning mechanisms?

Humans have exceptional abilities to learn new skills, manipulate tools and objects, and interact with our environment. In order to be successful at these tasks, our brain has developed learning mechanisms to deal with and compensate for the constantly changing dynamics of the world. If this mechanism or mechanisms can be understood from a computational point of view, then they can also be used to drive the adaptability and learning of robots. In this paper, we will present a new technique for examining changes in the feedforward motor command due to adaptation. This technique can then be utilized for examining motor adaptation in humans and determining a computational algorithm which explains motor learning. © 2007.