Judgments of path, not heading, guide locomotion

To steer a course through the world, people are almost entirely dependent on visual information, of which a key component is optic flow. In many models of locomotion, heading is described as the fundamental control variable; however, it has also been shown that fixating points along or near one's future path could be the basis of an efficient control solution. Here, the authors aim to establish how well observers can pinpoint instantaneous heading and path, by measuring their accuracy when looking at these features while traveling along straight and curved paths. The results showed that observers could identify both heading and path accurately (similar to 3 degrees) when traveling along straight paths, but on curved paths they were more accurate at identifying a point on their future path (similar to 5 degrees) than indicating their instantaneous heading (similar to 13 degrees). Furthermore, whereas participants could track changes in the tightness of their path, they were unable to accurately track the rate of change of heading. In light of these results, the authors suggest it is unlikely that heading is primarily used by the visual system to support active steering.

An automated calibration method for non-see-through head mounted displays

Accurate calibration of a head mounted display (HMD) is essential both for research on the visual system and for realistic interaction with virtual objects. Yet, existing calibration methods are time consuming and depend on human judgements, making them error prone. The methods are also limited to optical see-through HMDs. Building on our existing HMD calibration method [1], we show here how it is possible to calibrate a non-see-through HMD. A camera is placed inside an HMD displaying an image of a regular grid, which is captured by the camera. The HMD is then removed and the camera, which remains fixed in position, is used to capture images of a tracked calibration object in various positions. The locations of image features on the calibration object are then re-expressed in relation to the HMD grid. This allows established camera calibration techniques to be used to recover estimates of the display’s intrinsic parameters (width, height, focal length) and extrinsic parameters (optic centre and orientation of the principal ray). We calibrated a HMD in this manner in both see-through and in non-see-through modes and report the magnitude of the errors between real image features and reprojected features. Our calibration method produces low reprojection errors and involves no error-prone human measurements.

A stable one-step-ahead predictive control of non-linear systems

In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input–output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.

Self-tuning property of state-space self tuners

The basic assumption from implicit self-tuning theory is that, for self tuning to occur, the control input obtained from the estimated system model converges to the value whic would be obtained if the system parameters were known. As as direct result of this, only certain control strategies are acceptable. Here a general rule for the self-tuning property of pole-placement self tuners is obtained, and previous strategies are shown to be special cases of this.

Reduced complexity set-point following in self-tuning control

An external input signal is incorporated into a self-tuning controller which, although it is based on a CARMA system model, employs a state-space framework for control law calculations. Steady-state set point following can then be accomplished even when only a recursive least squares parameter estimation scheme is used, despite the fact that the disturbance affecting the system may well be coloured.

An automated calibration method for non-see-through head mounted displays

Accurate calibration of a head mounted display (HMD) is essential both for research on the visual system and for realistic interaction with virtual objects. Yet, existing calibration methods are time consuming and depend on human judgements, making them error prone, and are often limited to optical see-through HMDs. Building on our existing approach to HMD calibration Gilson et al. (2008), we show here how it is possible to calibrate a non-see-through HMD. A camera is placed inside a HMD displaying an image of a regular grid, which is captured by the camera. The HMD is then removed and the camera, which remains fixed in position, is used to capture images of a tracked calibration object in multiple positions. The centroids of the markers on the calibration object are recovered and their locations re-expressed in relation to the HMD grid. This allows established camera calibration techniques to be used to recover estimates of the HMD display's intrinsic parameters (width, height, focal length) and extrinsic parameters (optic centre and orientation of the principal ray). We calibrated a HMD in this manner and report the magnitude of the errors between real image features and reprojected features. Our calibration method produces low reprojection errors without the need for error-prone human judgements.

Nonlinear error dynamics for cycled data assimilation methods

We investigate the error dynamics for cycled data assimilation systems, such that the inverse problem of state determination is solved at tk, k = 1, 2, 3, ..., with a first guess given by the state propagated via a dynamical system model from time tk − 1 to time tk. In particular, for nonlinear dynamical systems that are Lipschitz continuous with respect to their initial states, we provide deterministic estimates for the development of the error ||ek|| := ||x(a)k − x(t)k|| between the estimated state x(a) and the true state x(t) over time. Clearly, observation error of size δ > 0 leads to an estimation error in every assimilation step. These errors can accumulate, if they are not (a) controlled in the reconstruction and (b) damped by the dynamical system under consideration. A data assimilation method is called stable, if the error in the estimate is bounded in time by some constant C. The key task of this work is to provide estimates for the error ||ek||, depending on the size δ of the observation error, the reconstruction operator Rα, the observation operator H and the Lipschitz constants K(1) and K(2) on the lower and higher modes of controlling the damping behaviour of the dynamics. We show that systems can be stabilized by choosing α sufficiently small, but the bound C will then depend on the data error δ in the form c||Rα||δ with some constant c. Since ||Rα|| → ∞ for α → 0, the constant might be large. Numerical examples for this behaviour in the nonlinear case are provided using a (low-dimensional) Lorenz '63 system.

Sensitivity of biogenic isoprene emissions to past, present and future environmental conditions and implications for atmospheric chemistry.

[1] We have implemented a process-based isoprene emission model in the HadGEM2 Earth-system model with coupled atmospheric chemistry in order to examine the feedback between isoprene emission and climate. Isoprene emissions and their impact on atmospheric chemistry and climate are estimated for preindustrial (1860–1869), present-day (2000–2009), and future (2100–2109) climate conditions. The estimate of 460 TgC/yr for present-day global total isoprene emission is consistent with previous estimates. Preindustrial isoprene emissions are estimated to be 26% higher than present-day. Future isoprene emissions using the RCP8.5 scenario are similar to present-day because increased emissions resulting from climate warming are countered by CO2 inhibition of isoprene emissions. The impact of biogenic isoprene emissions on the global O3 burden and CH4 lifetime is small but locally significant, and the impact of changes in isoprene emissions on atmospheric chemistry depends strongly on the state of climate and chemistry.

Performance analysis of AF cooperative systems with HPA nonlinearity in semi-blind relays

In this paper, dual-hop amplify-and-forward (AF) cooperative systems in the presence of high-power amplifier (HPA) nonlinearity at semi-blind relays, are investigated. Based on the modified AF cooperative system model taking into account the HPA nonlinearity, the expression for the output signal-to-noise ratio (SNR) at the destination node is derived, where the interference due to both the AF relaying mechanism and the HPA nonlinearity is characterized. The performance of the AF cooperative system under study is evaluated in terms of average symbol error probability (SEP), which is derived using the moment-generating function (MGF) approach, considering transmissions over Nakagami-m fading channels. Numerical results are provided and show the effects of some system parameters, such as the HPA parameters, numbers of relays, quadrature amplitude modulation (QAM) order, Nakagami parameters, on performance.

Exploring the climatic impact of the continental vegetation on the Mezosoic atmospheric CO2 and climate history

In this contribution, we continue our exploration of the factors defining the Mesozoic climatic history. We improve the Earth system model GEOCLIM designed for long term climate and geochemical reconstructions by adding the explicit calculation of the biome dynamics using the LPJ model. The coupled GEOCLIM-LPJ model thus allows the simultaneous calculation of the climate with a 2-D spatial resolution, the coeval atmospheric CO2, and the continental biome distribution. We found that accounting for the climatic role of the continental vegetation dynamics (albedo change, water cycle and surface roughness modulations) strongly affects the reconstructed geological climate. Indeed the calculated partial pressure of atmospheric CO2 over the Mesozoic is twice the value calculated when assuming a uniform constant vegetation. This increase in CO2 is triggered by a global cooling of the continents, itself triggered by a general increase in continental albedo owing to the development of desertic surfaces. This cooling reduces the CO2 consumption through silicate weathering, and hence results in a compensating increase in the atmospheric CO2 pressure. This study demonstrates that the impact of land plants on climate and hence on atmospheric CO2 is as important as their geochemical effect through the enhancement of chemical weathering of the continental surface. Our GEOCLIM-LPJ simulations also define a climatic baseline for the Mesozoic, around which exceptionally cool and warm events can be identified.

An oceanic origin for the increase of atmospheric radiocarbon during the Younger Dryas

Variations in carbon-14 to carbon-12 ratio in the atmosphere (Δ14Catm) provide a powerful diagnostic for elucidating the timing and nature of geophysical and anthropological change. The (Atlantic) marine archive suggests a rapid Δ14Catm increase of 50‰ at the onset of the Younger Dryas (YD) cold reversal (12.9–11.7 kyr BP), which has not yet been satisfactorily explained in terms of magnitude or causal mechanism, as either a change in ocean ventilation or production rate. Using Earth-system model simulations and comparison of marine-based radiocarbon records from different ocean basins, we demonstrate that the YD Δ14Catm increase is smaller than suggested by the marine archive. This is due to changes in reservoir age, predominantly caused by reduced ocean ventilation.

Towards radiocarbon calibration beyond 28ka using speleothems from the Bahamas

We present a new speleothem record of atmospheric Δ14C between 28 and 44 ka that offers considerable promise for resolving some of the uncertainty associated with existing radiocarbon calibration curves for this time period. The record is based on a comprehensive suite of AMS 14C ages, using new low-blank protocols, and U–Th ages using high precision MC-ICPMS procedures. Atmospheric Δ14C was calculated by correcting 14C ages with a constant dead carbon fraction (DCF) of 22.7 ± 5.9%, based on a comparison of stalagmite 14C ages with the IntCal04 (Reimer et al., 2004) calibration curve between 15 and 11 ka. The new Δ14C speleothem record shows similar structure and amplitude to that derived from Cariaco Basin foraminifera (Hughen et al., 2004, 2006), and the match is further improved if the latter is tied to the most recent Greenland ice core chronology (Svensson et al., 2008). These data are however in conflict with a previously published 14C data set for a stalagmite record from the Bahamas — GB-89-24-1 (Beck et al., 2001), which likely suffered from 14C analytical blank subtraction issues in the older part of the record. The new Bahamas speleothem ∆14C data do not show the extreme shifts between 44 and 40 ka reported in the previous study (Beck et al., 2001). Causes for the observed structure in derived atmospheric Δ14C variation based on the new speleothem data are investigated with a suite of simulations using an earth system model of intermediate complexity. Data-model comparison indicates that major fluctuations in atmospheric ∆14C during marine isotope stage 3 is primarily a function of changes in geomagnetic field intensity, although ocean–atmosphere system reorganisation also played a supporting role.

Predictability of large interannual Arctic sea-ice anomalies

In projections of twenty-first century climate, Arctic sea ice declines and at the same time exhibits strong interannual anomalies. Here, we investigate the potential to predict these strong sea-ice anomalies under a perfect-model assumption, using the Max-Planck-Institute Earth System Model in the same setup as in the Coupled Model Intercomparison Project Phase 5 (CMIP5). We study two cases of strong negative sea-ice anomalies: a 5-year-long anomaly for present-day conditions, and a 10-year-long anomaly for conditions projected for the middle of the twenty-first century. We treat these anomalies in the CMIP5 projections as the truth, and use exactly the same model configuration for predictions of this synthetic truth. We start ensemble predictions at different times during the anomalies, considering lagged-perfect and sea-ice-assimilated initial conditions. We find that the onset and amplitude of the interannual anomalies are not predictable. However, the further deepening of the anomaly can be predicted for typically 1 year lead time if predictions start after the onset but before the maximal amplitude of the anomaly. The magnitude of an extremely low summer sea-ice minimum is hard to predict: the skill of the prediction ensemble is not better than a damped-persistence forecast for lead times of more than a few months, and is not better than a climatology forecast for lead times of two or more years. Predictions of the present-day anomaly are more skillful than predictions of the mid-century anomaly. Predictions using sea-ice-assimilated initial conditions are competitive with those using lagged-perfect initial conditions for lead times of a year or less, but yield degraded skill for longer lead times. The results presented here suggest that there is limited prospect of predicting the large interannual sea-ice anomalies expected to occur throughout the twenty-first century.

A simulation of the last glacial maximum climate using the NCAR-CCSM

The National Center for Atmospheric Research-Community Climate System Model (NCAR-CCSM) is used in a coupled atmosphere–ocean–sea-ice simulation of the Last Glacial Maximum (LGM, around 21,000 years ago) climate. In the tropics, the simulation shows a moderate cooling of 3 °C over land and 2 °C in the ocean in zonal average. This cooling is about 1 °C cooler than the CLIMAP sea surface temperatures (SSTs) but consistent with recent estimates of both land and sea surface temperature changes. Subtropical waters are cooled by 2–2.5 °C, also in agreement with recent estimates. The simulated oceanic thermohaline circulation at the LGM is not only shallower but also weaker than the modern with a migration of deep-water formation site in the North Atlantic as suggested by the paleoceanographic evidences. The simulated northward flow of Antarctic Bottom Water (AABW) is enhanced. These deep circulation changes are attributable to the increased surface density flux in the Southern Ocean caused by sea-ice expansion at the LGM. Both the Gulf Stream and the Kuroshio are intensified due to the overall increase of wind stress over the subtropical oceans. The intensified zonal wind stress and southward shift of its maximum in the Southern Ocean effectively enhances the transport of the Antarctic Circumpolar Current (ACC) by more than 50%. Simulated SSTs are lowered by up to 8 °C in the midlatitudes. Simulated conditions in the North Atlantic are warmer and with less sea-ice than indicated by CLIMAP again, in agreement with more recent estimates. The increased meridional SST gradient at the LGM results in an enhanced Hadley Circulation and increased midlatitude storm track precipitation. The increased baroclinic storm activity also intensifies the meridional atmospheric heat transport. A sensitivity experiment shows that about half of the simulated tropical cooling at the LGM originates from reduced atmospheric concentrations of greenhouse gases.