A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Disturbance attenuation in linear systems via dynamical compensators: A parametric eigenstructure assignment approach

A simple approach is proposed for disturbance attenuation in multivariable linear systems via dynamical output compensators based on complete parametric eigenstructure assignment. The basic idea is to minimise the H-2 norm of the disturbance-output transfer function using the design freedom provided by eigenstructure assignment. For robustness, the closed-loop system is restricted to be nondefective. Besides the design parameters, the closed-loop eigenvalues are also optimised within desired regions on the left-half complex plane to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications can be easily achieved. As a demonstration, robust pole assignment, in the sense that the closed-loop eigenvalues are as insensitive as possible to open-loop system parameter perturbations, is treated. Application of the proposed approach to robust control of a magnetic bearing with a pair of opposing electromagnets and a rigid rotor is discussed.

The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusion

Polymer extrusion is one of the major methods of processing polymer materials and advanced process monitoring is important to ensure good product quality. However, commonly used process monitoring devices, e.g. temperature and pressure sensors, are limited in providing information on process dynamics inside an extruder barrel. Screw load torque dynamics, which may occur due to changes in solids conveying, melting, mixing, melt conveying, etc., are believed to be a useful indicator of process fluctuations inside the extruder barrel. However, practical measurement of the screw load torque is difficult to achieve. In this work, inferential monitoring of the screw load torque signal in an extruder was shown to be possible by monitoring the motor current (armature and/or field) and simulation studies were used to check the accuracy of the proposed method. The ability of this signal to aid identification and diagnosis of process issues was explored through an experimental investigation. Power spectral density and wavelet frequency analysis were implemented together with a covariance analysis. It was shown that the torque signal is dominated by the solid friction in the extruder and hence it did not correlate well with melting fluctuations. However, it is useful for online identification of solids conveying issues.

Components of Shame and Eating Disturbance among Clinical and Non-Clinical Populations

OBJECTIVE: To examine the association between components of shame (characterological, behavioural and bodily) and eating disturbance.

METHOD: This was a cross sectional study of 859 female and 256 male participants from the general population [non-clinical (NCP)] and 167 female participants from an eating disordered population [clinical (CP)] completing the Experience of Shame Scale. The NCP samples also completed the Eating Attitudes Test-26, and the CP samples completed the Eating Disorder Risk Composite of the Eating Disorder Inventory-3. Participants were recruited via schools/colleges, eating disorder charities and the Internet.

RESULTS: Bodily and characterological shame were independently predictive of eating disturbance in female NCP samples (both, p?<?.001); bodily shame was uniquely predictive of eating disturbance for the male NCP (p?<?.05) and female CP samples (p?<?.001).

CONCLUSION: The aetiology of eating disturbance may be different for male and female NCP samples. The male NCP and the female CP samples displayed a similar pathway to eating disturbance. It is important to acknowledge the different components of shame associated with eating disturbance in different populations.

Trait assembly in plant assemblages and its modulation by productivity and disturbance

Understanding how communities assemble is a key challenge in ecology. Conflicting hypotheses suggest that plant traits within communities should show divergence to reflect strategies to reduce competition or convergence to reflect strong selection for the environmental conditions operating. Further hypotheses suggest that plant traits related to productivity show convergence within communities, but those related to disturbance show divergence. Data on functional diversity (FD ) of 12 traits from 30 communities ranging from arable fields, mown and grazed grasslands to moorland and woodland were employed to test this using randomisations tests and correlation and regression analysis. No traits showed consistent significant convergence or divergence in functional diversity. When correlated to measures of the environment, the most common pattern was for functional diversity to decline (7 out of 12 traits) and the degree of convergence (7 out of 12 traits) to increase as the levels of productivity (measured as primary productivity, soil nitrogen release and vegetation C:N) and disturbance increased. Convergence or a relationship between functional diversity and the environment was not seen for a number of important traits, such as LDMC and SLA, which are considered as key predictors of ecosystem function. The analysis indicates that taking into account functional diversity within a system may be a necessary part of predicting the relationship between plant traits and ecosystem function, and that this may be of particular importance within less productive and less disturbed systems. © 2011 Springer-Verlag.

Robust food supply supply chains:An integrated framework for vulnerability assessment and disturbance management

The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

Micro-arthropod communities under human disturbance: is taxonomic aggregation a valuable tool for detecting multivariate change? Evidence from Mediterranean soil oribatid coenoses

Animal communities are sensitive to environmental disturbance, and several multivariate methods have recently been developed to detect changes in community structure. The complex taxonomy of soil invertebrates constrains the use of the community level in monitoring environmental changes, since species identification requires expertise and time. However, recent literature data on marine communities indicate that little multivariate information is lost in the taxonomic aggregation of species data to high rank taxa. In the present paper, this hypothesis was tested on two oribatid mite (oribatida, Acari) assemblages under two different kinds of disturbance: metal pollution and fires. Results indicate that data sets built at the genus and family systematic rank can detect the effects of disturbance with little loss of information. This is an encouraging result in view of the use of the community level as a preliminary tool for describing patterns of human-disturbed soil ecosystems. (c) 2006 Elsevier SAS. All rights reserved.

A school based study of psychological disturbance in children following the Omagh bomb

Objective
To assess the extent and nature of psychiatric morbidity among children (aged 8 to 13 years) 15 months after a car bomb explosion in the town of Omagh, Northern Ireland.

Method
A survey was conducted of 1945 school children attending 13 schools in the Omagh district. Questionnaires included demographic details, measures of exposure, the Horowitz Impact of Events Scale, the Birleson Self-Rating Depression Scale, and the Spence Children’s Anxiety Scale.

Results
Children directly exposed to the bomb reported higher levels of probable PTSD (70%), and psychological distress than those not exposed. Direct exposure was more closely associated with an increase in PTSD symptoms than in general psychiatric distress. Significant predictors of increased IES scores included being male, witnessing people injured and reporting a perceived life threat but when co-morbid anxiety and depression are included as potential predictors anxiety remains the only significant predictor of PTSD scores.

Conclusions
School-based studies are a potentially valuable means of screening and assessing for PTSD in children after large-scale tragedies. Assessment should consider type of exposure, perceived life threat and other co-morbid anxiety as risk factors for PTSD.

Physiotherapy for Sleep Disturbance in People With Chronic Low Back Pain:Results of a Feasibility Randomized Controlled Trial

Objective: To determine the feasibility of a randomized controlled trial investigating the effectiveness of physiotherapy for sleep disturbance in chronic low back pain (CLBP) (=12wks). Design: Randomized controlled trial with evaluations at baseline, 3 months, and 6 months. Setting: Outpatient physiotherapy department in an academic teaching hospital. Participants: Participants with CLBP were randomly assigned to a walking program (n=20; mean age ± SD, 46.4±13.8y), supervised exercise class (n=20; mean age ± SD, 41.3±11.9y), or usual physiotherapy (n=20; mean age ± SD, 47.1±14.3y). The 3-month evaluation was completed by 44 participants (73%), and 42 (70%) participants completed the 6-month evaluation. Interventions: Participants received a physiotherapy-delivered 8-week walking program, an 8-week group supervised exercise class (1 class/wk), or 1-to-1 usual physiotherapy (advice, manual therapy, and exercise). Main Outcome Measures: Sleep was assessed by the self-reported Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Pittsburgh Sleep Diary, and objective actigraphy. Results: Groups were comparable at baseline. Most (95%, n=57) of the participants had sleep disturbance. The acceptability of actigraphy was excellent at baseline (58 of 60 participants), but dropped at 3 months (26 of 44 participants). There were improvements on the PSQI and ISI in all groups at 3 and 6 months, with predominantly medium effect sizes (Cohen d=0.2-0.5). Conclusions: The high prevalence of sleep disturbance indicated the feasibility of good recruitment in future trials. The PSQI would be a suitable screening tool and outcome measure alongside an objective nonobtrusive sleep outcome measure. The effectiveness of physiotherapy for sleep disturbance in CLBP warrants investigation in a fully powered randomized controlled trial. © 2013 American Congress of Rehabilitation Medicine.