Predictive control using feedback linearization based on dynamic neural models

This paper presents a hybrid control strategy integrating dynamic neural networks and feedback linearization into a predictive control scheme. Feedback linearization is an important nonlinear control technique which transforms a nonlinear system into a linear system using nonlinear transformations and a model of the plant. In this work, empirical models based on dynamic neural networks have been employed. Dynamic neural networks are mathematical structures described by differential equations, which can be trained to approximate general nonlinear systems. A case study based on a mixing process is presented.

Intelligent agents and distributed models for cooperative task support

Purpose – To describe some research done, as part of an EPSRC funded project, to assist engineers working together on collaborative tasks. Design/methodology/approach – Distributed finite state modelling and agent techniques are used successfully in a new hybrid self-organising decision making system applied to collaborative work support. For the particular application, analysis of the tasks involved has been performed and these tasks are modelled. The system then employs a novel generic agent model, where task and domain knowledge are isolated from the support system, which provides relevant information to the engineers. Findings – The method is applied in the despatch of transmission commands within the control room of The National Grid Company Plc (NGC) – tasks are completed significantly faster when the system is utilised. Research limitations/implications – The paper describes a generic approach and it would be interesting to investigate how well it works in other applications. Practical implications – Although only one application has been studied, the methodology could equally be applied to a general class of cooperative work environments. Originality/value – One key part of the work is the novel generic agent model that enables the task and domain knowledge, which are application specific, to be isolated from the support system, and hence allows the method to be applied in other domains.

A review and implementation of swarm pattern formation and transformation models

Purpose: The purpose of this paper is to address a classic problem – pattern formation identified by researchers in the area of swarm robotic systems – and is also motivated by the need for mathematical foundations in swarm systems. Design/methodology/approach: The work is separated out as inspirations, applications, definitions, challenges and classifications of pattern formation in swarm systems based on recent literature. Further, the work proposes a mathematical model for swarm pattern formation and transformation. Findings: A swarm pattern formation model based on mathematical foundations and macroscopic primitives is proposed. A formal definition for swarm pattern transformation and four special cases of transformation are introduced. Two general methods for transforming patterns are investigated and a comparison of the two methods is presented. The validity of the proposed models, and the feasibility of the methods investigated are confirmed on the Traer Physics and Processing environment. Originality/value: This paper helps in understanding the limitations of existing research in pattern formation and the lack of mathematical foundations for swarm systems. The mathematical model and transformation methods introduce two key concepts, namely macroscopic primitives and a mathematical model. The exercise of implementing the proposed models on physics simulator is novel.

Models for evolving networks: with applications in telecommunication and online activities

Driven by a range of modern applications that includes telecommunications, e-business and on-line social interaction, recent ideas in complex networks can be extended to the case of time-varying connectivity. Here we propose a general frame- work for modelling and simulating such dynamic networks, and we explain how the long time behaviour may reveal important information about the mechanisms underlying the evolution.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

A statistical mechanical approach for the computation of the climatic response to general forcings

The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. In this paper we show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied with great success to analyze the climatic response to general forcings. The crucial value of the Ruelle theory lies in the fact that it allows to compute the response of the system in terms of expectation values of explicit and computable functions of the phase space averaged over the invariant measure of the unperturbed state. We choose as test bed a classical version of the Lorenz 96 model, which, in spite of its simplicity, has a well-recognized prototypical value as it is a spatially extended one-dimensional model and presents the basic ingredients, such as dissipation, advection and the presence of an external forcing, of the actual atmosphere. We recapitulate the main aspects of the general response theory and propose some new general results. We then analyze the frequency dependence of the response of both local and global observables to perturbations having localized as well as global spatial patterns. We derive analytically several properties of the corresponding susceptibilities, such as asymptotic behavior, validity of Kramers-Kronig relations, and sum rules, whose main ingredient is the causality principle. We show that all the coefficients of the leading asymptotic expansions as well as the integral constraints can be written as linear function of parameters that describe the unperturbed properties of the system, such as its average energy. Some newly obtained empirical closure equations for such parameters allow to define such properties as an explicit function of the unperturbed forcing parameter alone for a general class of chaotic Lorenz 96 models. We then verify the theoretical predictions from the outputs of the simulations up to a high degree of precision. The theory is used to explain differences in the response of local and global observables, to define the intensive properties of the system, which do not depend on the spatial resolution of the Lorenz 96 model, and to generalize the concept of climate sensitivity to all time scales. We also show how to reconstruct the linear Green function, which maps perturbations of general time patterns into changes in the expectation value of the considered observable for finite as well as infinite time. Finally, we propose a simple yet general methodology to study general Climate Change problems on virtually any time scale by resorting to only well selected simulations, and by taking full advantage of ensemble methods. The specific case of globally averaged surface temperature response to a general pattern of change of the CO2 concentration is discussed. We believe that the proposed approach may constitute a mathematically rigorous and practically very effective way to approach the problem of climate sensitivity, climate prediction, and climate change from a radically new perspective.

The International Urban Energy Balance Models Comparison Project: First Results from Phase 1

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no com- parison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling ap- proaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux.

Comparing tube models for predicting the linear rheology of branched polymer melts

The hierarchical and "bob" (or branch-on-branch) models are tube-based computational models recently developed for predicting the linear rheology of general mixtures of polydisperse branched polymers. These two models are based on a similar tube-theory framework but differ in their numerical implementation and details of relaxation mechanisms. We present a detailed overview of the similarities and differences of these models and examine the effects of these differences on the predictions of the linear viscoelastic properties of a set of representative branched polymer samples in order to give a general picture of the performance of these models. Our analysis confirms that the hierarchical and bob models quantitatively predict the linear rheology of a wide range of branched polymer melts but also indicate that there is still no unique solution to cover all types of branched polymers without case-by-case adjustment of parameters such as the dilution exponent alpha and the factor p(2) which defines the hopping distance of a branch point relative to the tube diameter. An updated version of the hierarchical model, which shows improved computational efficiency and refined relaxation mechanisms, is introduced and used in these analyses.

Eyes, amygdala, and other models of face processing: Questions for the SIMS model

This commentary raises general questions about the parsimony and generalizability of the SIMS model, before interrogating the specific roles that the amygdala and eye contact play in it. Additionally, this situates the SIMS model alongside another model of facial expression processing, with a view to incorporating individual differences in emotion perception.

Global climate change and soil carbon stocks: predictions from two contrasting models for the turnover of organic carbon in soil

Enhanced release of CO2 to the atmosphere from soil organic carbon as a result of increased temperatures may lead to a positive feedback between climate change and the carbon cycle, resulting in much higher CO2 levels and accelerated lobal warming. However, the magnitude of this effect is uncertain and critically dependent on how the decomposition of soil organic C (heterotrophic respiration) responds to changes in climate. Previous studies with the Hadley Centre’s coupled climate–carbon cycle general circulation model (GCM) (HadCM3LC) used a simple, single-pool soil carbon model to simulate the response. Here we present results from numerical simulations that use the more sophisticated ‘RothC’ multipool soil carbon model, driven with the same climate data. The results show strong similarities in the behaviour of the two models, although RothC tends to simulate slightly smaller changes in global soil carbon stocks for the same forcing. RothC simulates global soil carbon stocks decreasing by 54 GtC by 2100 in a climate change simulation compared with an 80 GtC decrease in HadCM3LC. The multipool carbon dynamics of RothC cause it to exhibit a slower magnitude of transient response to both increased organic carbon inputs and changes in climate. We conclude that the projection of a positive feedback between climate and carbon cycle is robust, but the magnitude of the feedback is dependent on the structure of the soil carbon model.

Towards an improved and more flexible representation of water stress in coupled photosynthesis–stomatal conductance models

Coupled photosynthesis–stomatal conductance (A–gs) models are commonly used in ecosystem models to represent the exchange rate of CO2 and H2O between vegetation and the atmosphere. The ways these models account for water stress differ greatly among modelling schemes. This study provides insight into the impact of contrasting model configurations of water stress on the simulated leaf-level values of net photosynthesis (A), stomatal conductance (gs), the functional relationship among them and their ratio, the intrinsic water use efficiency (A/gs), as soil dries. A simple, yet versatile, normalized soil moisture dependent function was used to account for the effects of water stress on gs, on mesophyll conductance (gm) and on the biochemical capacity. Model output was compared to leaf-level values obtained from the literature. The sensitivity analyses emphasized the necessity to combine both stomatal and non-stomatal limitations of A in coupled A–gs models to accurately capture the observed functional relationships A vs. gs and A/gsvs. gs in response to drought. Accounting for water stress in coupled A–gs models by imposing either stomatal or biochemical limitations of A, as commonly practiced in most ecosystem models, failed to reproduce the observed functional relationship between key leaf gas exchange attributes. A quantitative limitation analysis revealed that the general pattern of C3 photosynthetic response to water stress may be well represented in coupled A–gs models by imposing the highest limitation strength to gm, then to gs and finally to the biochemical capacity.

The general observation period 2007 within the priority program on quantitative precipitation forecasting: concept and first results

In the year 2007 a General Observation Period (GOP) has been performed within the German Priority Program on Quantitative Precipitation Forecasting (PQP). By optimizing the use of existing instrumentation a large data set of in-situ and remote sensing instruments with special focus on water cycle variables was gathered over the full year cycle. The area of interest covered central Europe with increasing focus towards the Black Forest where the Convective and Orographically-induced Precipitation Study (COPS) took place from June to August 2007. Thus the GOP includes a variety of precipitation systems in order to relate the COPS results to a larger spatial scale. For a timely use of the data, forecasts of the numerical weather prediction models COSMO-EU and COSMO-DE of the German Meteorological Service were tailored to match the observations and perform model evaluation in a near real-time environment. The ultimate goal is to identify and distinguish between different kinds of model deficits and to improve process understanding.

A general basis for quarter-power scaling in animals

It has been known for decades that the metabolic rate of animals scales with body mass with an exponent that is almost always <1, >2/3, and often very close to 3/4. The 3/4 exponent emerges naturally from two models of resource distribution networks, radial explosion and hierarchically branched, which incorporate a minimum of specific details. Both models show that the exponent is 2/3 if velocity of flow remains constant, but can attain a maximum value of 3/4 if velocity scales with its maximum exponent, 1/12. Quarterpower scaling can arise even when there is no underlying fractality. The canonical “fourth dimension” in biological scaling relations can result from matching the velocity of flow through the network to the linear dimension of the terminal “service volume” where resources are consumed. These models have broad applicability for the optimal design of biological and engineered systems where energy, materials, or information are distributed from a single source.

Predictability of the western North Pacific summer climate demonstrated by the coupled models of ENSEMBLES

The Asian monsoon system, including the western North Pacific (WNP), East Asian, and Indian monsoons, dominates the climate of the Asia-Indian Ocean-Pacific region, and plays a significant role in the global hydrological and energy cycles. The prediction of monsoons and associated climate features is a major challenge in seasonal time scale climate forecast. In this study, a comprehensive assessment of the interannual predictability of the WNP summer climate has been performed using the 1-month lead retrospective forecasts (hindcasts) of five state-of-the-art coupled models from ENSEMBLES for the period of 1960–2005. Spatial distribution of the temporal correlation coefficients shows that the interannual variation of precipitation is well predicted around the Maritime Continent and east of the Philippines. The high skills for the lower-tropospheric circulation and sea surface temperature (SST) spread over almost the whole WNP. These results indicate that the models in general successfully predict the interannual variation of the WNP summer climate. Two typical indices, the WNP summer precipitation index and the WNP lower-tropospheric circulation index (WNPMI), have been used to quantify the forecast skill. The correlation coefficient between five models’ multi-model ensemble (MME) mean prediction and observations for the WNP summer precipitation index reaches 0.66 during 1979–2005 while it is 0.68 for the WNPMI during 1960–2005. The WNPMI-regressed anomalies of lower-tropospheric winds, SSTs and precipitation are similar between observations and MME. Further analysis suggests that prediction reliability of the WNP summer climate mainly arises from the atmosphere–ocean interaction over the tropical Indian and the tropical Pacific Ocean, implying that continuing improvement in the representation of the air–sea interaction over these regions in CGCMs is a key for long-lead seasonal forecast over the WNP and East Asia. On the other hand, the prediction of the WNP summer climate anomalies exhibits a remarkable spread resulted from uncertainty in initial conditions. The summer anomalies related to the prediction spread, including the lower-tropospheric circulation, SST and precipitation anomalies, show a Pacific-Japan or East Asia-Pacific pattern in the meridional direction over the WNP. Our further investigations suggest that the WNPMI prediction spread arises mainly from the internal dynamics in air–sea interaction over the WNP and Indian Ocean, since the local relationships among the anomalous SST, circulation, and precipitation associated with the spread are similar to those associated with the interannual variation of the WNPMI in both observations and MME. However, the magnitudes of these anomalies related to the spread are weaker, ranging from one third to a half of those anomalies associated with the interannual variation of the WNPMI in MME over the tropical Indian Ocean and subtropical WNP. These results further support that the improvement in the representation of the air–sea interaction over the tropical Indian Ocean and subtropical WNP in CGCMs is a key for reducing the prediction spread and for improving the long-lead seasonal forecast over the WNP and East Asia.

Fit for planning? An evaluation of the application of development viability appraisal models in the UK planning system

The aim of this paper is to critically examine the application of development appraisal to viability assessment in the planning system. This evaluation is of development appraisal models in general and also their use in particular applications associated with estimating planning obligation capacity. The paper is organised into four themes: · The context and conceptual basis for development viability appraisal · A review of development viability appraisal methods · A discussion of selected key inputs into a development viability appraisal · A discussion of the applications of development viability appraisals in the planning system It is assumed that readers are familiar with the basic models and information needs of development viability appraisal rather than at the cutting edge of practice and/or academe