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Sample records for predicting local control

  1. Local Model Predictive Control for T-S Fuzzy Systems.

    Science.gov (United States)

    Lee, Donghwan; Hu, Jianghai

    2017-09-01

    In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem. The local stability analysis, the estimation of the domain of attraction, and feasibility of the proposed MPC are proved. Examples are given to demonstrate the advantages of the suggested MPC over existing approaches.

  2. Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics.

    Science.gov (United States)

    Zhao, Meng; Ding, Baocang

    2015-03-01

    This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Stereotactic radiotherapy following surgery for brain metastasis: Predictive factors for local control and radionecrosis.

    Science.gov (United States)

    Doré, M; Martin, S; Delpon, G; Clément, K; Campion, L; Thillays, F

    2017-02-01

    To evaluate local control and adverse effects after postoperative hypofractionated stereotactic radiosurgery in patients with brain metastasis. We reviewed patients who had hypofractionated stereotactic radiosurgery (7.7Gy×3 prescribed to the 70% isodose line, with 2mm planning target volume margin) following resection from March 2008 to January 2014. The primary endpoint was local failure defined as recurrence within the surgical cavity. Secondary endpoints were distant failure rates and the occurrence of radionecrosis. Out of 95 patients, 39.2% had metastatic lesions from a non-small cell lung cancer primary tumour. The median Graded Prognostic Assessment score was 3 (48% of patients). One-year local control rates were 84%. Factors associated with improved local control were no cavity enhancement on pre-radiation MRI (P<0.00001), planning target volume less than 12cm 3 (P=0.005), Graded Prognostic Assessment score 2 or above (P=0.009). One-year distant cerebral control rates were 56%. Thirty-three percent of patients received whole brain radiation therapy. Histologically proven radionecrosis of brain tissue occurred in 7.2% of cases. The size of the preoperative lesion and the volume of healthy brain tissue receiving 21Gy (V 21 ) were both predictive of the incidence of radionecrosis (P=0.010 and 0.036, respectively). Adjuvant hypofractionated stereotactic radiosurgery to the postoperative cavity in patients with brain metastases results in excellent local control in selected patients, helps delay the use of whole brain radiation, and is associated with a relatively low risk of radionecrosis. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

  4. Singlet oxygen explicit dosimetry to predict local tumor control for HPPH-mediated photodynamic therapy

    Science.gov (United States)

    Penjweini, Rozhin; Kim, Michele M.; Ong, Yi Hong; Zhu, Timothy C.

    2017-02-01

    This preclinical study examines four dosimetric quantities (light fluence, photosensitizer photobleaching ratio, PDT dose, and reacted singlet oxygen ([1O2]rx)) to predict local control rate (LCR) for 2-(1-Hexyloxyethyl)-2-devinyl pyropheophorbide (HPPH)-mediated photodynamic therapy (PDT). Mice bearing radiation-induced fibrosarcoma (RIF) tumors were treated with different in-air fluences (135, 250 and 350 J/cm2) and in-air fluence rates (50, 75 and 150 mW/cm2) at 0.25 mg/kg HPPH and a drug-light interval of 24 hours using a 1 cm diameter collimated laser beam at 665 nm wavelength. A macroscopic model was used to calculate ([1O2]rx)) based on in vivo explicit dosimetry of the initial tissue oxygenation, photosensitizer concentration, and tissue optical properties. PDT dose was defined as a temporal integral of drug concentration and fluence rate (φ) at a 3 mm tumor depth. Light fluence rate was calculated throughout the treatment volume based on Monte-Carlo simulation and measured tissue optical properties. The tumor volume of each mouse was tracked for 30 days after PDT and Kaplan-Meier analyses for LCR were performed based on a tumor volume <=100 mm3, for four dose metrics: fluence, HPPH photobleaching rate, PDT dose, and ([1O2]rx)). The results of this study showed that ([1O2]rx)) is the best dosimetric quantity that can predict tumor response and correlate with LCR.

  5. Positron Emission Tomography (PET) Evaluation After Initial Chemotherapy and Radiation Therapy Predicts Local Control in Rhabdomyosarcoma

    Energy Technology Data Exchange (ETDEWEB)

    Dharmarajan, Kavita V., E-mail: dharmark@mskcc.org [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States); Wexler, Leonard H.; Gavane, Somali; Fox, Josef J.; Schoder, Heiko; Tom, Ashlyn K.; Price, Alison N.; Meyers, Paul A.; Wolden, Suzanne L. [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States)

    2012-11-15

    Purpose: 18-fluorodeoxyglucose positron emission tomography (PET) is already an integral part of staging in rhabdomyosarcoma. We investigated whether primary-site treatment response characterized by serial PET imaging at specific time points can be correlated with local control. Patients and Methods: We retrospectively examined 94 patients with rhabdomyosarcoma who received initial chemotherapy 15 weeks (median) before radiotherapy and underwent baseline, preradiation, and postradiation PET. Baseline PET standardized uptake values (SUVmax) and the presence or absence of abnormal uptake (termed PET-positive or PET-negative) both before and after radiation were examined for the primary site. Local relapse-free survival (LRFS) was calculated according to baseline SUVmax, PET-positive status, and PET-negative status by the Kaplan-Meier method, and comparisons were tested with the log-rank test. Results: The median patient age was 11 years. With 3-year median follow-up, LRFS was improved among postradiation PET-negative vs PET-positive patients: 94% vs 75%, P=.02. By contrast, on baseline PET, LRFS was not significantly different for primary-site SUVmax {<=}7 vs >7 (median), although the findings suggested a trend toward improved LRFS: 96% for SUVmax {<=}7 vs 79% for SUVmax >7, P=.08. Preradiation PET also suggested a statistically insignificant trend toward improved LRFS for PET-negative (97%) vs PET-positive (81%) patients (P=.06). Conclusion: Negative postradiation PET predicted improved LRFS. Notably, 77% of patients with persistent postradiation uptake did not experience local failure, suggesting that these patients could be closely followed up rather than immediately referred for intervention. Negative baseline and preradiation PET findings suggested statistically insignificant trends toward improved LRFS. Additional study may further understanding of relationships between PET findings at these time points and outcome in rhabdomyosarcoma.

  6. Optimizing operation costs of the heating system of a household using model predictive control considering a local PV installation

    DEFF Research Database (Denmark)

    Koch-Ciobotaru, Cosmin; Isleifsson, Fridrik Rafn; Gehrke, Oliver

    2012-01-01

    This paper presents a model predictive controller developed in order to minimize the cost of grid energy consumption and maximize the amount of energy consumed from a local photovoltaic (PV) installation. The usage of as much locally produced renewable energy sources (RES) as possible, diminishes...... the effects of their large penetration in the distribution grid and reduces overloading the grid capacity, which is an increasing problem for the power system. The controller uses 24 hour prediction data for the ambient temperature, the solar irradiance, and for the PV output power. Simulation results...

  7. Radiotherapy of tonsillar and base of the tongue carcinoma. Prediction of local control

    NARCIS (Netherlands)

    Mak-Kregar, S.; Baris, G.; Lebesque, J. V.; Balm, A. J.; Hart, A. A.; Hilgers, F. J.

    1993-01-01

    119 patients with squamous cell carcinoma of the tonsillar region (68) and the base of the tongue (51), who received external radiotherapy with curative intent between 1966 and 1984, are analysed with respect to overall treatment results, local tumour control and prognostic factors. Radiation doses

  8. The role of Ki67 proliferation assessment in predicting local control in bladder cancer patients treated by radical radiation therapy

    International Nuclear Information System (INIS)

    Lara, P.C.; Gonzalez, G.; Rey, A.; Apolinario, R.; Santana, C.; Afonso, J.L.; Diaz, J.M.

    1998-01-01

    Purpose: To assess whether tumour proliferation as measured by Ki67 immunostaining has any predictive value for local control in bladder cancer patients treated by radiotherapy. Patients and methods: Fifty-five patients suffering from infiltrating bladder carcinoma recommended for radical radiotherapy (66 Gy/6-7weeks) were included in this study. Paraffin-embedded pre-treatment tumour sections were stained with the Ki67 antibody. The percentage of Ki67-positive nuclei was correlated with established prognostic factors, local control and survival. Results27%) Ki67 expression indices (31.5%) (P<0.05; log-rank test). Conclusions: Ki67 immunostaining was a feasible method to estimate tumour proliferation. Patients with very low proliferating tumours seemed to achieve better local control after fractionated radiotherapy compared to other patients. Further studies are needed with a greater number of patients to accurately define the role of Ki67 expression in predicting tumour repopulation during fractionated radiotherapy. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)

  9. Is sterilisation of the operating theatre, after radio-chemotherapy of locally advanced oesophageal cancers, predictive of a better local control?

    International Nuclear Information System (INIS)

    Loubiere, Amandine

    2011-01-01

    Purpose and objectives: To search if the pathological complete response (pCR) of the 102 patients treated at the University Hospital Center of Tours between 1990 and 2010 with concomitant radio-chemotherapy for an esophageal cancer is correlated to an increase of local control, with correct R0 resection and acceptable mortality rate. To analyze the Impact of histological tumor or nodal down-staging on the loco regional control and the disease free survival. Search if there are some predictive factors of pCR. Materials and methods: The combined preoperative treatment was based on an association of two cycles of 5FU R and cisplatin R with concomitant radiotherapy at the dose of 40 to 44 Gy. The survival curves of both recurrence free survival and disease free survival were calculated and then analyzed according to the histological response. Results: With a mean follow-up of 38 months, 70 patients were dead, 47 of their cancer. Thirty patients were still alive and 26 without recurrence. The postoperative mortality and morbidity rates were respectively of 53% and 27%. The median of survival was estimated to 27 months. Overall survival (p= 0.33), disease free survival (p= 0.14), were analysed with no statistical difference between our 3 groups (pCR, near pCR and other). However, there was an interest in doing the combined treatment for the responders (p R , Cisplatin R , and external beam radiotherapy at the dose of 40 to 44 Gy for the patients with a locally advanced esophageal cancer allow us to obtain the same results on survival, tolerance, morbidity and mortality rates than in the literature. The pCR seems to increase the local control and the disease free survival. Tumor or nodal down-staging is a major prognostic factor. (author)

  10. Singlet oxygen explicit dosimetry to predict long-term local tumor control for BPD-mediated photodynamic therapy

    Science.gov (United States)

    Kim, Michele M.; Penjweini, Rozhin; Ong, Yi Hong; Zhu, Timothy C.

    2017-02-01

    Photodynamic therapy (PDT) is a well-established treatment modality for cancer and other malignant diseases; however, quantities such as light fluence, photosensitizer photobleaching rate, and PDT dose do not fully account for all of the dynamic interactions between the key components involved. In particular, fluence rate (Φ) effects are not accounted for, which has a large effect on the oxygen consumption rate. In this preclinical study, reacted singlet oxygen [1O2]rx was investigated as a dosimetric quantity for PDT outcome. The ability of [1O2]rx to predict the long-term local tumor control rate (LCR) for BPD-mediated PDT was examined. Mice bearing radioactivelyinduced fibrosarcoma (RIF) tumors were treated with different in-air fluences (250, 300, and 350 J/cm2) and in-air ϕ (75, 100, and150 mW/cm2) with a BPD dose of 1 mg/kg and a drug-light interval of 3 hours. Treatment was delivered with a collimated laser beam of 1 cm diameter at 690 nm. Explicit dosimetry of initial tissue oxygen concentration, tissue optical properties, and BPD concentration was used to calculate [1O2]rx. Φ was calculated for the treatment volume based on Monte-Carlo simulations and measured tissue optical properties. Kaplan-Meier analyses for LCR were done for an endpoint of tumor volume defined as the product of the timeintegral of photosensitizer concentration and Φ at a 3 mm tumor depth. Preliminary studies show that [1O2]rx better correlates with LCR and is an effective dosimetric quantity that can predict treatment outcome.

  11. Singlet oxygen explicit dosimetry to predict long-term local tumor control for Photofrin-mediated photodynamic therapy

    Science.gov (United States)

    Penjweini, Rozhin; Kim, Michele M.; Ong, Yi Hong; Zhu, Timothy C.

    2017-02-01

    Although photodynamic therapy (PDT) is an established modality for the treatment of cancer, current dosimetric quantities do not account for the variations in PDT oxygen consumption for different fluence rates (φ). In this study we examine the efficacy of reacted singlet oxygen concentration ([1O2]rx) to predict long-term local control rate (LCR) for Photofrin-mediated PDT. Radiation-induced fibrosarcoma (RIF) tumors in the right shoulders of female C3H mice are treated with different in-air fluences of 225-540 J/cm2 and in-air fluence rate (φair) of 50 and 75 mW/cm2 at 5 mg/kg Photofrin and a drug-light interval of 24 hours using a 1 cm diameter collimated laser beam at 630 nm wavelength. [1O2]rx is calculated by using a macroscopic model based on explicit dosimetry of Photofrin concentration, tissue optical properties, tissue oxygenation and blood flow changes during PDT. The tumor volume of each mouse is tracked for 90 days after PDT and Kaplan-Meier analyses for LCR are performed based on a tumor volume defined as a temporal integral of photosensitizer concentration and Φ at a 3 mm tumor depth. φ is calculated throughout the treatment volume based on Monte-Carlo simulation and measured tissue optical properties. Our preliminary studies show that [1O2]rx is the best dosimetric quantity that can predict tumor response and correlate with LCR. Moreover, [1O2]rx calculated using the blood flow changes was in agreement with [1O2]rx calculated based on the actual tissue oxygenation.

  12. Control of dynamical localization

    International Nuclear Information System (INIS)

    Gong Jiangbin; Woerner, Hans Jakob; Brumer, Paul

    2003-01-01

    Control over the quantum dynamics of chaotic kicked rotor systems is demonstrated. Specifically, control over a number of quantum coherent phenomena is achieved by a simple modification of the kicking field. These include the enhancement of the dynamical localization length, the introduction of classical anomalous diffusion assisted control for systems far from the semiclassical regime, and the observation of a variety of strongly nonexponential line shapes for dynamical localization. The results provide excellent examples of controlled quantum dynamics in a system that is classically chaotic and offer opportunities to explore quantum fluctuations and correlations in quantum chaos

  13. Local control room

    CERN Multimedia

    CERN PhotoLab

    1972-01-01

    Local control room in the ejection building : all electronics pertaining to proton distribution and concomitants such as beam gymnastics and diagnostics at high energies will eventually be gathered here. Shown is the first of two rows of fast ejection electronic racks. It includes only what is necessary for operation.

  14. Applied predictive control

    CERN Document Server

    Sunan, Huang; Heng, Lee Tong

    2002-01-01

    The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

  15. Local control stations

    International Nuclear Information System (INIS)

    Brown, W.S.; Higgins, J.C.; Wachtel, J.A.

    1993-01-01

    This paper describes research concerning the effects of human engineering design at local control stations (i.e., operator interfaces located outside the control room) on human performance and plant safety. The research considered both multifunction panels (e.g. remote shutdown panels) as well as single-function interfaces (e.g., valves, breakers, gauges, etc.). Changes in performance shaping factors associated with variations in human engineering at LCSs were estimated based on expert opinion. By means of a scaling procedure, these estimates were used to modify the human error probabilities in a PRA model, which was then employed to generate estimates of plant risk and scoping-level value/impact ratios for various human engineering upgrades. Recent documentation of human engineering deficiencies at single-function LCSs was also reviewed, and an assessment of the current status of LCSs with respect to human engineering was conducted

  16. Comparative Analysis of Local Control Prediction Using Different Biophysical Models for Non-Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy

    Directory of Open Access Journals (Sweden)

    Bao-Tian Huang

    2017-01-01

    Full Text Available Purpose. The consistency for predicting local control (LC data using biophysical models for stereotactic body radiotherapy (SBRT treatment of lung cancer is unclear. This study aims to compare the results calculated from different models using the treatment planning data. Materials and Methods. Treatment plans were designed for 17 patients diagnosed with primary non-small cell lung cancer (NSCLC using 5 different fraction schemes. The Martel model, Ohri model, and the Tai model were used to predict the 2-year LC value. The Gucken model, Santiago model, and the Tai model were employed to estimate the 3-year LC data. Results. We found that the employed models resulted in completely different LC prediction except for the Gucken and the Santiago models which exhibited quite similar 3-year LC data. The predicted 2-year and 3-year LC values in different models were not only associated with the dose normalization but also associated with the employed fraction schemes. The greatest difference predicted by different models was up to 15.0%. Conclusions. Our results show that different biophysical models influence the LC prediction and the difference is not only correlated to the dose normalization but also correlated to the employed fraction schemes.

  17. LocTree3 prediction of localization

    DEFF Research Database (Denmark)

    Goldberg, T.; Hecht, M.; Hamp, T.

    2014-01-01

    The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria a...

  18. Support Vector Machine-Based Prediction of Local Tumor Control After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

    International Nuclear Information System (INIS)

    Klement, Rainer J.; Allgäuer, Michael; Appold, Steffen; Dieckmann, Karin; Ernst, Iris; Ganswindt, Ute; Holy, Richard; Nestle, Ursula; Nevinny-Stickel, Meinhard; Semrau, Sabine; Sterzing, Florian; Wittig, Andrea; Andratschke, Nicolaus; Guckenberger, Matthias

    2014-01-01

    Background: Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. Methods and Materials: We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performance by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Results: Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED ISO ) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED ISO and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED ISO , age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. Conclusions: These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are

  19. Support Vector Machine-Based Prediction of Local Tumor Control After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Klement, Rainer J., E-mail: rainer_klement@gmx.de [Department of Radiation Oncology, University of Würzburg (Germany); Department of Radiotherapy and Radiation Oncology, Leopoldina Hospital, Schweinfurt (Germany); Allgäuer, Michael [Department of Radiotherapy, Barmherzige Brüder Regensburg, Regensburg (Germany); Appold, Steffen [Department of Radiation Oncology, Technische Universität Dresden (Germany); Dieckmann, Karin [Department of Radiotherapy, Medical University of Vienna (Austria); Ernst, Iris [Department of Radiotherapy, University Hospital Münster (Germany); Ganswindt, Ute [Department of Radiation Oncology, Ludwigs-Maximilians-University Munich, München (Germany); Holy, Richard [Department of Radiation Oncology, RWTH Aachen University, Aachen (Germany); Nestle, Ursula [Department of Radiation Oncology, University Hospital Freiburg, Freiburg i Br (Germany); Nevinny-Stickel, Meinhard [Department of Therapeutic Radiology and Oncology, Innsbruck Medical University (Austria); Semrau, Sabine [Department of Radiation Oncology, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen (Germany); Sterzing, Florian [Department of Radiation Oncology, University Hospital Heidelberg (Germany); Wittig, Andrea [Department of Radiotherapy and Radiation Oncology, Philipps-University Marburg (Germany); Andratschke, Nicolaus [Department of Radiation Oncology, Technische Universität München (Germany); Guckenberger, Matthias [Department of Radiation Oncology, University of Würzburg (Germany)

    2014-03-01

    Background: Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. Methods and Materials: We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performance by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Results: Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED{sub ISO}) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED{sub ISO} and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED{sub ISO}, age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. Conclusions: These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP

  20. SPE dose prediction using locally weighted regression

    International Nuclear Information System (INIS)

    Hines, J. W.; Townsend, L. W.; Nichols, T. F.

    2005-01-01

    When astronauts are outside earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events (SPEs). The total dose received from a major SPE in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be mitigated with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train and provides predictions as accurate as neural network models previously used. (authors)

  1. SPE dose prediction using locally weighted regression

    International Nuclear Information System (INIS)

    Hines, J. W.; Townsend, L. W.; Nichols, T. F.

    2005-01-01

    When astronauts are outside Earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events. The total dose received from a major solar particle event in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be reduced with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train, and provides predictions as accurate as the neural network models that were used previously. (authors)

  2. Incoherent control of locally controllable quantum systems

    International Nuclear Information System (INIS)

    Dong Daoyi; Zhang Chenbin; Rabitz, Herschel; Pechen, Alexander; Tarn, T.-J.

    2008-01-01

    An incoherent control scheme for state control of locally controllable quantum systems is proposed. This scheme includes three steps: (1) amplitude amplification of the initial state by a suitable unitary transformation, (2) projective measurement of the amplified state, and (3) final optimization by a unitary controlled transformation. The first step increases the amplitudes of some desired eigenstates and the corresponding probability of observing these eigenstates, the second step projects, with high probability, the amplified state into a desired eigenstate, and the last step steers this eigenstate into the target state. Within this scheme, two control algorithms are presented for two classes of quantum systems. As an example, the incoherent control scheme is applied to the control of a hydrogen atom by an external field. The results support the suggestion that projective measurements can serve as an effective control and local controllability information can be used to design control laws for quantum systems. Thus, this scheme establishes a subtle connection between control design and controllability analysis of quantum systems and provides an effective engineering approach in controlling quantum systems with partial controllability information.

  3. Generalized Predictive Control and Neural Generalized Predictive Control

    Directory of Open Access Journals (Sweden)

    Sadhana CHIDRAWAR

    2008-12-01

    Full Text Available As Model Predictive Control (MPC relies on the predictive Control using a multilayer feed forward network as the plants linear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. This paper presents a detailed derivation of the Generalized Predictive Control and Neural Generalized Predictive Control with Newton-Raphson as minimization algorithm. Taking three separate systems, performances of the system has been tested. Simulation results show the effect of neural network on Generalized Predictive Control. The performance comparison of this three system configurations has been given in terms of ISE and IAE.

  4. Neural Network Classifiers for Local Wind Prediction.

    Science.gov (United States)

    Kretzschmar, Ralf; Eckert, Pierre; Cattani, Daniel; Eggimann, Fritz

    2004-05-01

    This paper evaluates the quality of neural network classifiers for wind speed and wind gust prediction with prediction lead times between +1 and +24 h. The predictions were realized based on local time series and model data. The selection of appropriate input features was initiated by time series analysis and completed by empirical comparison of neural network classifiers trained on several choices of input features. The selected input features involved day time, yearday, features from a single wind observation device at the site of interest, and features derived from model data. The quality of the resulting classifiers was benchmarked against persistence for two different sites in Switzerland. The neural network classifiers exhibited superior quality when compared with persistence judged on a specific performance measure, hit and false-alarm rates.

  5. Embedded controllers for local board-control

    CERN Document Server

    Neufeld, Niko; Mini, Giuseppe; Sannino, Mario; Guzik, Zbigniew; Jacobsson, Richard; Jost, Beat

    2005-01-01

    The LHCb experiment at CERN has a large number of custom electronic boards performing high-speed data-processing. Like in any large experiment the control and monitoring of these crate-mounted boards must be integrated into the overall control-system. Traditionally this has been done by using buses like VME on the back-plane of the crates. LHCb has chosen to equip every board with an embedded micro-controller and connecting them in a large Local Area Network. The intelligence of these devices allows complex (soft) real-time control and monitoring, required for modern powerful FPGA driven electronics. Moreover each board has its own, isolated control access path, which increases the robustness of the entire system. The system is now in pre-production at several sites and will go into full production during next year. The hardware and software will be discussed and experiences from the R&D and pre-production will be reviewed, with an emphasis on advantages and difficulties of this approach to board-control.

  6. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  7. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  8. Residual {sup 18}F-FDG-PET Uptake 12 Weeks After Stereotactic Ablative Radiotherapy for Stage I Non-Small-Cell Lung Cancer Predicts Local Control

    Energy Technology Data Exchange (ETDEWEB)

    Bollineni, Vikram Rao, E-mail: v.r.bollineni@umcg.nl [Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen (Netherlands); Widder, Joachim [Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen (Netherlands); Pruim, Jan [Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen (Netherlands); Langendijk, Johannes A.; Wiegman, Erwin M. [Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen (Netherlands)

    2012-07-15

    Purpose: To investigate the prognostic value of [{sup 18}F]fluorodeoxyglucose positron emission tomography (FDG-PET) uptake at 12 weeks after stereotactic ablative radiotherapy (SABR) for stage I non-small-cell lung cancer (NSCLC). Methods and Materials: From November 2006 to February 2010, 132 medically inoperable patients with proven Stage I NSCLC or FDG-PET-positive primary lung tumors were analyzed retrospectively. SABR consisted of 60 Gy delivered in 3 to 8 fractions. Maximum standardized uptake value (SUV{sub max}) of the treated lesion was assessed 12 weeks after SABR, using FDG-PET. Patients were subsequently followed at regular intervals using computed tomography (CT) scans. Association between post-SABR SUV{sub max} and local control (LC), mediastinal failure, distant failure, overall survival (OS), and disease-specific survival (DSS) was examined. Results: Median follow-up time was 17 months (range, 3-40 months). Median lesion size was 25 mm (range, 9-70 mm). There were 6 local failures: 15 mediastinal failures, 15 distant failures, 13 disease-related deaths, and 16 deaths from intercurrent diseases. Glucose corrected post-SABR median SUV{sub max} was 3.0 (range, 0.55-14.50). Using SUV{sub max} 5.0 as a cutoff, the 2-year LC was 80% versus 97.7% for high versus low SUV{sub max}, yielding an adjusted subhazard ratio (SHR) for high post-SABR SUV{sub max} of 7.3 (95% confidence interval [CI], 1.4-38.5; p = 0.019). Two-year DSS rates were 74% versus 91%, respectively, for high and low SUV{sub max} values (SHR, 2.2; 95% CI, 0.8-6.3; p = 0.113). Two-year OS was 62% versus 81% (hazard ratio [HR], 1.6; 95% CI, 0.7-3.7; p = 0.268). Conclusions: Residual FDG uptake (SUV{sub max} {>=}5.0) 12 weeks after SABR signifies increased risk of local failure. A single FDG-PET scan at 12 weeks could be used to tailor further follow-up according to the risk of failure, especially in patients potentially eligible for salvage surgery.

  9. Signal peptides and protein localization prediction

    DEFF Research Database (Denmark)

    Nielsen, Henrik

    2005-01-01

    In 1999, the Nobel prize in Physiology or Medicine was awarded to Gunther Blobel “for the discovery that proteins have intrinsic signals that govern their transport and localization in the cell”. Since the subcellular localization of a protein is an important clue to its function, the characteriz...

  10. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  11. Local and Integral Control of Workload

    NARCIS (Netherlands)

    M.B.M. de Koster (René); J. Wijngaard (Jacob)

    1989-01-01

    textabstractIn most of the literature on performance analysis of production systems, buffer are assumed to be controlled locally. In automated production systems buffers are not always the result of local physical space restrictions, but may also be software- controlled. Software-controlled buffers

  12. Control of territorial communities in local government

    Directory of Open Access Journals (Sweden)

    О. А. Смоляр

    2015-11-01

    Full Text Available According to Art. 5 of the Constitution of Ukraine all power in Ukraine belong to people, which is primary, unified, inalienable and carried people through free will through elections, referendum and other forms of direct democracy, including those intended to control the activity of bodies and officials of the government and local government. Paper objective. At the local level the main supervisory entity in local government is local community. Consolidation of the Constitution of Ukraine the primary subject of local self-government territorial community not only meets current international practice, but also the historical traditions of Ukrainian people. Control territorial community in all phases of local government is one of the most important functions of managing the development of appropriate settlements, and therefore needs an effective mechanism of legal regulation, clearly define mutual rights and responsibilities of controlling and controlled entities. Recent research and publications analysis. Problems Assessment of local communities and the activities of local government officials in their works viewed Y.G. Barabash, P.M. Liubchenko, O.D. Skopych, Y.P. Strilets. However, given the variety of aspects of this area of research remain many questions that need resolving, on which depends largely on the further process of local governance. The paper main body. The existing regulation territorial communities can exercise control in local government actually only through local governments. The control of the executive bodies of village, town council municipalities can only be made through the appropriate council. The existing regulation of territorial communities can exercise control in local government actually only through local governments. The control of the executive bodies of village, town council municipalities can only be made through the appropriate council. The author emphasizes that only by implementing self-control powers local

  13. Globalization and localization of Management Control Systems

    DEFF Research Database (Denmark)

    Toldbod, Thomas; Israelsen, Poul

    2014-01-01

    Through an empirical case study this article examines the operation of multiple management control systems as a package in a Danish manufacturing company. The analysis focuses on four different management control systems; cybernetic controls, planning controls, reward controls, and administrative...... have more particular characteristics. Specifically, this study finds that cybernetic controls and administrative controls are designed as global management control systems. Planning controls are glocal systems and reward & compensation controls assume local characteristics. The finding leads...... controls, through the theoretical lens of globalization, localization, and glocalization. The analysis documents that these different management control systems are affected differently by the processes of globalization and localization, whereby some are universal throughout the organization and others...

  14. Localized climate control in greenhouses

    NARCIS (Netherlands)

    Booij, P.S.; Sijs, J.; Fransman, J.E.

    2012-01-01

    Strategies for controlling the indoor climate in greenhouses are based on a few sensors and actuators in combination with an assumption that climate variables, such as temperature, are uniform throughout the greenhouse. While this is already an improper assumption for conventional greenhouses, it

  15. Predicting local field potentials with recurrent neural networks.

    Science.gov (United States)

    Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

    2016-08-01

    We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

  16. Survivin Expression as a Predictive Marker for Local Control in Patients With High-Risk T1 Bladder Cancer Treated With Transurethral Resection and Radiochemotherapy

    International Nuclear Information System (INIS)

    Weiss, Christian; Roemer, Felix von; Capalbo, Gianni; Ott, Oliver J.; Wittlinger, Michael; Krause, Steffen F.; Sauer, Rolf; Roedel, Claus; Roedel, Franz

    2009-01-01

    Purpose: The objectives of this study were to investigate the expression of survivin in tumor samples from patients with high-risk T1 bladder cancer and to correlate its expression with clinicopathologic features as well as clinical outcomes after initial transurethral resection (TURBT) followed by radiotherapy (RT) or radiochemotherapy (RCT). Methods and Materials: Survivin protein expression was evaluated by immunohistochemistry on tumor specimen (n = 48) from the initial TURBT, and was correlated with clinical and histopathologic characteristics as well as with 5-year rates of local failure, tumor progression, and death from urothelial cancer after primary bladder sparring treatment with RT/RCT. Results: Survivin was not expressed in normal bladder urothelium but was overexpressed in 67% of T1 tumors. No association between survivin expression and clinicopathologic factors (age, gender, grading, multifocality, associated carcinoma in situ) could be shown. With a median follow-up of 27 months (range, 3-140 months), elevated survivin expression was significantly associated with an increased probability of local failure after TURBT and RCT/RT (p = 0.003). There was also a clear trend toward a higher risk of tumor progression (p = 0.07) and lower disease-specific survival (p = 0.10). Conclusions: High survivin expression is a marker of tumor aggressiveness and may help to identify a subgroup of patients with T1 bladder cancer at a high risk for recurrence when treated with primary organ-sparing approaches such as TURBT and RCT.

  17. Data-Based Predictive Control with Multirate Prediction Step

    Science.gov (United States)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  18. SCADA system with predictive controller applied to irrigation canals

    OpenAIRE

    Figueiredo, João; Botto, Miguel; Rijo, Manuel

    2013-01-01

    This paper applies a model predictive controller (MPC) to an automatic water canal with sensors and actuators controlled by a network (programmable logic controller), and supervised by a SCADA system (supervisory control and a data acquisition). This canal is composed by a set of distributed sub-systems that control the water level in each canal pool, constrained by discharge gates (control variables) and water off-takes (disturbances). All local controllers are available through an industria...

  19. Quality Controlled Local Climatological Data (QCLCD) Publication

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quality Controlled Local Climatological Data (QCLCD) contains summaries from major airport weather stations that include a daily account of temperature extremes,...

  20. Local Geomagnetic Indices and the Prediction of Auroral Power

    Science.gov (United States)

    Newell, P. T.; Gjerloev, J. W.

    2014-12-01

    As the number of magnetometer stations and data processing power increases, just how auroral power relates to geomagnetic observations becomes a quantitatively more tractable question. This paper compares Polar UVI auroral power observations during 1997 with a variety of geomagnetic indices. Local time (LT) versions of the SuperMAG auroral electojet (SME) are introduced and examined, along with the corresponding upper and lower envelopes (SMU and SML). Also, the East-West component, BE, is investigated. We also consider whether using any of the local indices is actually better at predicting local auroral power than a single global index. Each index is separated into 24 LT indices based on a sliding 3-h MLT window. The ability to predict - or better reconstruct - auroral power varies greatly with LT, peaking at 1900 MLT, where about 75% of the variance (r2) can be predicted at 1-min cadence. The aurora is fairly predictable from 1700 MLT - 0400 MLT, roughly the region in which substorms occur. Auroral power is poorly predicted from auroral electrojet indices from 0500 MLT - 1500 MLT, with the minima at 1000-1300 MLT. In the region of high predictability, the local variable which works best is BE, in contrast to long-standing expectations. However using global SME is better than any local variable. Auroral power is best predicted by combining global SME with a local index: BE from 1500-0200 MLT, and either SMU or SML from 0300-1400 MLT. In the region of the diffuse aurora, it is better to use a 30 min average than the cotemporaneous 1-min SME value, while from 1500-0200 MLT the cotemporaneous 1-min SME works best, suggesting a more direct physical relationship with the auroral circuit. These results suggest a significant role for discrete auroral currents closing locally with Pedersen currents.

  1. Edge localized modes control: experiment and theory

    Energy Technology Data Exchange (ETDEWEB)

    Bedoulet, M.; Huysmans, G.; Thomas, P.; Joffrin, E.; Rimini, F.; Monier-Garbet, P.; Grosman, A.; Ghendrih, P. [Association Euratom-CEA, Centre d' Etudes de Cadarache, 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee; Parail, V.; Lomas, P.; Matthews, G.; Wilson, H.; Gryaznevich, M.; Gonsell, G.; Loarte, A.; Saibene, G.; Sartori, R.; Leonard, A.; Snyder, P.; Evans, T.; Gohil, P.; Burell, H.; Moyer, R.; Kamada, Y.; Oyama, N.; Hatae, T.; Degeling, A.; Martin, Y.; Lister, J.; Rapp, J.; Perez, C.; Lang, P.; Chankin, A.; Eich, T.; Sips, A.; Stober, J.; Horton, L.; Kallenbach, A.; Suttrop, W.; Saarelma, S.; Cowley, S.; Lonnroth, J.; Kamiya, K.; Shimada, M.; Polevoi, A.; Federici, G

    2004-07-01

    The paper reviews recent theoretical and experimental results focusing on the identification of the key factors controlling ELM (energy localized mode) energy and particle losses both in natural ELMs and in the presence of external controlling mechanisms. The theoretical description of the most studied Type-I ELMs is progressing from linear MHD stability analysis for peeling and ballooning modes to the non-linear explosive models and transport codes. Present theories cannot predict the ELM size self-consistently, however they pointed out the benefit of the high plasma shaping, high q{sub 95} and high pedestal density in reducing the ELM affected area. The experimental data also suggest that the conductive energy losses in Type-I ELM can be controlled by working in specific plasma conditions. In particular, the existence of purely convective small Type-I ELMs regimes at high q{sub 95} (>4.5) with {delta}W{sub ELM}/W{sub ped}<5% was demonstrated in high triangularity ({delta} {approx} 0.5) plasmas in JET. Small benign ELMs regimes in present machines (EDA, HRS, Type-II, grassy, QH, Type-III in impurity seeded discharges at high {delta} and their relevance for ITER parameters are reviewed briefly. The absence of already developed ITER relevant high confinement scenarios with acceptable ELMs has motivated recent intensive experimental and theoretical studies of active control of ELMs. The possibility of suppression of Type-I ELMs in H-mode scenarios at constant confinement was demonstrated in DIII-D experiments with a stochastic boundary created by external coils. It has been demonstrated in AUG that small pellets can trigger Type-I ELMs with a frequency imposed by the pellet injector. Pellet induced ELMs are similar to the intrinsic Type-I ELMs with the same frequency. At the same time the confinement degradation due to the fuelling can be minimized with pellets small as compared to the gas injection. Recent plasma current ramp experiments (JET, COMPASS-D) and

  2. Edge localized modes control: experiment and theory

    International Nuclear Information System (INIS)

    Bedoulet, M.; Huysmans, G.; Thomas, P.; Joffrin, E.; Rimini, F.; Monier-Garbet, P.; Grosman, A.; Ghendrih, P.; Parail, V.; Lomas, P.; Matthews, G.; Wilson, H.; Gryaznevich, M.; Gonsell, G.; Loarte, A.; Saibene, G.; Sartori, R.; Leonard, A.; Snyder, P.; Evans, T.; Gohil, P.; Burell, H.; Moyer, R.; Kamada, Y.; Oyama, N.; Hatae, T.; Degeling, A.; Martin, Y.; Lister, J.; Rapp, J.; Perez, C.; Lang, P.; Chankin, A.; Eich, T.; Sips, A.; Stober, J.; Horton, L.; Kallenbach, A.; Suttrop, W.; Saarelma, S.; Cowley, S.; Lonnroth, J.; Kamiya, K.; Shimada, M.; Polevoi, A.; Federici, G.

    2004-01-01

    The paper reviews recent theoretical and experimental results focusing on the identification of the key factors controlling ELM (energy localized mode) energy and particle losses both in natural ELMs and in the presence of external controlling mechanisms. The theoretical description of the most studied Type-I ELMs is progressing from linear MHD stability analysis for peeling and ballooning modes to the non-linear explosive models and transport codes. Present theories cannot predict the ELM size self-consistently, however they pointed out the benefit of the high plasma shaping, high q 95 and high pedestal density in reducing the ELM affected area. The experimental data also suggest that the conductive energy losses in Type-I ELM can be controlled by working in specific plasma conditions. In particular, the existence of purely convective small Type-I ELMs regimes at high q 95 (>4.5) with ΔW ELM /W ped <5% was demonstrated in high triangularity (δ ∼ 0.5) plasmas in JET. Small benign ELMs regimes in present machines (EDA, HRS, Type-II, grassy, QH, Type-III in impurity seeded discharges at high δ and their relevance for ITER parameters are reviewed briefly. The absence of already developed ITER relevant high confinement scenarios with acceptable ELMs has motivated recent intensive experimental and theoretical studies of active control of ELMs. The possibility of suppression of Type-I ELMs in H-mode scenarios at constant confinement was demonstrated in DIII-D experiments with a stochastic boundary created by external coils. It has been demonstrated in AUG that small pellets can trigger Type-I ELMs with a frequency imposed by the pellet injector. Pellet induced ELMs are similar to the intrinsic Type-I ELMs with the same frequency. At the same time the confinement degradation due to the fuelling can be minimized with pellets small as compared to the gas injection. Recent plasma current ramp experiments (JET, COMPASS-D) and modelling (JETTO) demonstrated that the edge

  3. Model Predictive Control for Load Frequency Control with Wind Turbines

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2015-01-01

    Full Text Available Reliable load frequency (LFC control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.

  4. Cervical Gross Tumor Volume Dose Predicts Local Control Using Magnetic Resonance Imaging/Diffusion-Weighted Imaging—Guided High-Dose-Rate and Positron Emission Tomography/Computed Tomography—Guided Intensity Modulated Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Dyk, Pawel; Jiang, Naomi; Sun, Baozhou; DeWees, Todd A. [Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri (United States); Fowler, Kathryn J.; Narra, Vamsi [Department of Diagnostic Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri (United States); Garcia-Ramirez, Jose L.; Schwarz, Julie K. [Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri (United States); Grigsby, Perry W., E-mail: pgrigsby@wustl.edu [Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri (United States); Division of Nuclear Medicine, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri (United States); Division of Gynecologic Oncology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri (United States); Alvin J. Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri (United States)

    2014-11-15

    Purpose: Magnetic resonance imaging/diffusion weighted-imaging (MRI/DWI)-guided high-dose-rate (HDR) brachytherapy and {sup 18}F-fluorodeoxyglucose (FDG) — positron emission tomography/computed tomography (PET/CT)-guided intensity modulated radiation therapy (IMRT) for the definitive treatment of cervical cancer is a novel treatment technique. The purpose of this study was to report our analysis of dose-volume parameters predicting gross tumor volume (GTV) control. Methods and Materials: We analyzed the records of 134 patients with International Federation of Gynecology and Obstetrics stages IB1-IVB cervical cancer treated with combined MRI-guided HDR and IMRT from July 2009 to July 2011. IMRT was targeted to the metabolic tumor volume and lymph nodes by use of FDG-PET/CT simulation. The GTV for each HDR fraction was delineated by use of T2-weighted or apparent diffusion coefficient maps from diffusion-weighted sequences. The D100, D90, and Dmean delivered to the GTV from HDR and IMRT were summed to EQD2. Results: One hundred twenty-five patients received all irradiation treatment as planned, and 9 did not complete treatment. All 134 patients are included in this analysis. Treatment failure in the cervix occurred in 24 patients (18.0%). Patients with cervix failures had a lower D100, D90, and Dmean than those who did not experience failure in the cervix. The respective doses to the GTV were 41, 58, and 136 Gy for failures compared with 67, 99, and 236 Gy for those who did not experience failure (P<.001). Probit analysis estimated the minimum D100, D90, and Dmean doses required for ≥90% local control to be 69, 98, and 260 Gy (P<.001). Conclusions: Total dose delivered to the GTV from combined MRI-guided HDR and PET/CT-guided IMRT is highly correlated with local tumor control. The findings can be directly applied in the clinic for dose adaptation to maximize local control.

  5. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  6. Analysis of locally controlled esophageal carcinomas treated with radiotherapy

    International Nuclear Information System (INIS)

    Gotoh, Yasuo; Yamada, Shogo; Takai, Yoshihiro; Nemoto, Kenji; Ogawa, Yoshihiro; Hoshi, Akihiko; Ariga, Hisanori; Sakamoto, Kiyohiko

    1996-01-01

    Of 227 esophageal carcinomas treated with a radiation dose of 60 Gy or more, 100 patients had no tumor or ulceration (with or without stenosis) of the esophagus after irradiation. We analyzed local control factors of these 100 patients to determine the need for further treatment. The cumulative local control rate at five years was 40% in all cases, 37% in 21 cases without any stenosis of the esophagus and 40% in 79 cases with stenosis. The presence of stenosis of the esophagus after irradiation was not a critical factor in predicting final local control. Local recurrence of tumors with findings of Borrmann III or Borrmann IV by the pretreatment esophageal barium study, tumors controlled after a total dose of more than 80 Gy, tumors without low dose rate telecobalt therapy (LDRT: 1 Gy/hour, 5 to 7 Gy/day, a total dose of 12 to 15 Gy) as boost therapy, and apparently controlled tumors with a stenotic ratio of 60% or more or with 5 cm or more length of stenosis of the esophagus after irradiation was significantly higher than that of the others (p<0.05). Multivariate analysis revealed that findings of pretreatment barium study, total dose, with or without LDRT, and length of stenosis of the esophagus after irradiation were significantly important factors in local control. Members of the high risk group of apparently controlled tumors should undertake surgical treatment or further intensive chemotherapy. (author)

  7. Protein subcellular localization prediction using artificial intelligence technology.

    Science.gov (United States)

    Nair, Rajesh; Rost, Burkhard

    2008-01-01

    Proteins perform many important tasks in living organisms, such as catalysis of biochemical reactions, transport of nutrients, and recognition and transmission of signals. The plethora of aspects of the role of any particular protein is referred to as its "function." One aspect of protein function that has been the target of intensive research by computational biologists is its subcellular localization. Proteins must be localized in the same subcellular compartment to cooperate toward a common physiological function. Aberrant subcellular localization of proteins can result in several diseases, including kidney stones, cancer, and Alzheimer's disease. To date, sequence homology remains the most widely used method for inferring the function of a protein. However, the application of advanced artificial intelligence (AI)-based techniques in recent years has resulted in significant improvements in our ability to predict the subcellular localization of a protein. The prediction accuracy has risen steadily over the years, in large part due to the application of AI-based methods such as hidden Markov models (HMMs), neural networks (NNs), and support vector machines (SVMs), although the availability of larger experimental datasets has also played a role. Automatic methods that mine textual information from the biological literature and molecular biology databases have considerably sped up the process of annotation for proteins for which some information regarding function is available in the literature. State-of-the-art methods based on NNs and HMMs can predict the presence of N-terminal sorting signals extremely accurately. Ab initio methods that predict subcellular localization for any protein sequence using only the native amino acid sequence and features predicted from the native sequence have shown the most remarkable improvements. The prediction accuracy of these methods has increased by over 30% in the past decade. The accuracy of these methods is now on par with

  8. Pretreatment tables predicting pathologic stage of locally advanced prostate cancer.

    Science.gov (United States)

    Joniau, Steven; Spahn, Martin; Briganti, Alberto; Gandaglia, Giorgio; Tombal, Bertrand; Tosco, Lorenzo; Marchioro, Giansilvio; Hsu, Chao-Yu; Walz, Jochen; Kneitz, Burkhard; Bader, Pia; Frohneberg, Detlef; Tizzani, Alessandro; Graefen, Markus; van Cangh, Paul; Karnes, R Jeffrey; Montorsi, Francesco; van Poppel, Hein; Gontero, Paolo

    2015-02-01

    Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. Retropubic RP and pelvic lymphadenectomy. Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  9. Local connectome phenotypes predict social, health, and cognitive factors

    Directory of Open Access Journals (Sweden)

    Michael A. Powell

    2018-03-01

    Full Text Available The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N = 841 of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions. The local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size within a voxel, and it reflects the proximal characteristics of white matter fascicles distributed throughout the brain. Here we show how variability in the local connectome is correlated in a principled way across individuals. This intersubject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This work shows, for the first time, how the local connectome has both the sensitivity and the specificity to

  10. Local knowledge of fishermen in weather prediction in Moa and ...

    African Journals Online (AJOL)

    This study investigated local knowledge of fishermen in weather prediction in Moa and Kwale coastal villages, Tanzania. Focus Group Discussions, Seasonal Calendars, Time line analysis, key informant interviews, questionnaire surveys and documentary reviews were used to gather data. The SPSS programme was used ...

  11. Predicting the nutritional health status of locally produced palm oil ...

    African Journals Online (AJOL)

    Three physical properties of locally produced palm oil – viscosity, thermal conductivity and density for varying temperatures were determined. The values obtained were compared with corresponding internationally stipulated standard values using statistics of mean and graphs. The purpose of the comparison was to predict ...

  12. Local dimension and finite time prediction in coupled map lattices

    Indian Academy of Sciences (India)

    Forecasting, for obvious reasons, often become the most important goal to be achieved. For spatially extended systems (e.g. atmospheric system) where the local nonlinearities lead to the most unpredictable chaotic evolution, it is highly desirable to have a simple diagnostic tool to identify regions of predictable behaviour.

  13. Electrochemotherapy increases local control after incomplete ...

    African Journals Online (AJOL)

    Ibrahim Eldaghayes

    2016-11-24

    Nov 24, 2016 ... The treatment was well tolerated, and the patient is still disease free after 12 months. ECT resulted in improved local control and should be considered among the available adjuvant treatments in equines carrying soft tissue tumors. Keywords: Cisplatin, Electrochemotherapy, Equine, Fibrosarcoma.

  14. Local quantum control of Heisenberg spin chains

    International Nuclear Information System (INIS)

    Heule, Rahel; Bruder, C.; Stojanovic, Vladimir M.; Burgarth, Daniel

    2010-01-01

    Motivated by some recent results of quantum control theory, we discuss the feasibility of local operator control in arrays of interacting qubits modeled as isotropic Heisenberg spin chains. Acting on one of the end spins, we aim at finding piecewise-constant control pulses that lead to optimal fidelities for a chosen set of quantum gates. We analyze the robustness of the obtained results for the gate fidelities to random errors in the control fields, finding that with faster switching between piecewise-constant controls the system is less susceptible to these errors. The observed behavior falls into a generic class of physical phenomena that are related to a competition between resonance- and relaxation-type behavior, exemplified by motional narrowing in NMR experiments. Finally, we discuss how the obtained optimal gate fidelities are altered when the corresponding rapidly varying piecewise-constant control fields are smoothened through spectral filtering.

  15. Analytical model for local scour prediction around hydrokinetic turbine foundations

    Science.gov (United States)

    Musa, M.; Heisel, M.; Hill, C.; Guala, M.

    2017-12-01

    Marine and Hydrokinetic renewable energy is an emerging sustainable and secure technology which produces clean energy harnessing water currents from mostly tidal and fluvial waterways. Hydrokinetic turbines are typically anchored at the bottom of the channel, which can be erodible or non-erodible. Recent experiments demonstrated the interactions between operating turbines and an erodible surface with sediment transport, resulting in a remarkable localized erosion-deposition pattern significantly larger than those observed by static in-river construction such as bridge piers, etc. Predicting local scour geometry at the base of hydrokinetic devices is extremely important during foundation design, installation, operation, and maintenance (IO&M), and long-term structural integrity. An analytical modeling framework is proposed applying the phenomenological theory of turbulence to the flow structures that promote the scouring process at the base of a turbine. The evolution of scour is directly linked to device operating conditions through the turbine drag force, which is inferred to locally dictate the energy dissipation rate in the scour region. The predictive model is validated using experimental data obtained at the University of Minnesota's St. Anthony Falls Laboratory (SAFL), covering two sediment mobility regimes (clear water and live bed), different turbine designs, hydraulic parameters, grain size distribution and bedform types. The model is applied to a potential prototype scale deployment in the lower Mississippi River, demonstrating its practical relevance and endorsing the feasibility of hydrokinetic energy power plants in large sandy rivers. Multi-turbine deployments are further studied experimentally by monitoring both local and non-local geomorphic effects introduced by a twelve turbine staggered array model installed in a wide channel at SAFL. Local scour behind each turbine is well captured by the theoretical predictive model. However, multi

  16. Evaluation and comparison of mammalian subcellular localization prediction methods

    Directory of Open Access Journals (Sweden)

    Fink J Lynn

    2006-12-01

    Full Text Available Abstract Background Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER, peroxisome, and lysosome. The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE

  17. A range-based predictive localization algorithm for WSID networks

    Science.gov (United States)

    Liu, Yuan; Chen, Junjie; Li, Gang

    2017-11-01

    Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

  18. Estimation and prediction under local volatility jump-diffusion model

    Science.gov (United States)

    Kim, Namhyoung; Lee, Younhee

    2018-02-01

    Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

  19. Local control after brachytherapy for localized prostatic carcinomas

    International Nuclear Information System (INIS)

    Wachter, T.; Peneau, M.; Sabattier, R.; Breteau, N.

    1996-01-01

    From 1991 to 1995; 31 patients (mid-age: 70 years) underwent prostatic brachytherapy for localized prostate cancers using Iridium 192 transperineal percutaneous interstitial implantation guided by transrectal ultrasonography. Initial staging included among other evaluations a bilateral staging, iliac and obturator lymph nodes dissection. Classification according to stage was : T1b=16%, T1c=36%, T2a=19%, T2b=13%, T2c=13%, T3a=3%. All patients were N (-). Gleason score was 5 for 55%. 77% of the initial PSA was < 25μg/l. Follow-up included one clinical control and psa determination at 1-3-6-12 and 18 months, bone scanning at 12 months and prostate biopsy guided by transrectal ultrasonography at 18, 24, 30 months. Up to now, mean follow-up is 32 months. At one month, psa was normal (< 2,5μg/l) in 21% of the patients, at 12 months 60% and 67% two years after brachytherapy. Biopsies at 18 months were negative for 60% of the patients and 63% at 24 months. 3 patients were metastased after 3 years. 4 patients had severe complications with colostomy and/or urinary derivation. This technic seems to be interesting for localized prostate cancers T1 and T2 with initial psa < 25μg/l. Two third of the patients had normal psa and negative biopsies after 2 years. The rate of ano-rectal and urinary morbidity is high but is explained by the technic used at the beginning of this study

  20. The time frame of Epstein-Barr virus latent membrane protein-1 gene to disappear in nasopharyngeal swabs after initiation of primary radiotherapy is an independently significant prognostic factor predicting local control for patients with nasopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Lin, S.-Y.; Chang, K.-P.; Hsieh, M.-S.; Ueng, S.-H.; Hao, S.-P.; Tseng, C.-K.; Pai, P.-C.; Chang, F.-T.; Tsai, M.-H.; Tsang, N.-M.

    2005-01-01

    Purpose: The presence of Epstein-Barr virus latent membrane protein-1 (LMP-1) gene in nasopharyngeal swabs indicates the presence of nasopharyngeal carcinoma (NPC) mucosal tumor cells. This study was undertaken to investigate whether the time taken for LMP-1 to disappear after initiation of primary radiotherapy (RT) was inversely associated with NPC local control. Methods and Materials: During July 1999 and October 2002, there were 127 nondisseminated NPC patients receiving serial examinations of nasopharyngeal swabbing with detection of LMP-1 during the RT course. The time for LMP-1 regression was defined as the number of days after initiation of RT for LMP-1 results to turn negative. The primary outcome was local control, which was represented by freedom from local recurrence. Results: The time for LMP-1 regression showed a statistically significant influence on NPC local control both univariately (p < 0.0001) and multivariately (p = 0.004). In multivariate analysis, the administration of chemotherapy conferred a significantly more favorable local control (p = 0.03). Advanced T status (≥ T2b), overall treatment time of external photon radiotherapy longer than 55 days, and older age showed trends toward being poor prognosticators. The time for LMP-1 regression was very heterogeneous. According to the quartiles of the time for LMP-1 regression, we defined the pattern of LMP-1 regression as late regression if it required 40 days or more. Kaplan-Meier plots indicated that the patients with late regression had a significantly worse local control than those with intermediate or early regression (p 0.0129). Conclusion: Among the potential prognostic factors examined in this study, the time for LMP-1 regression was the most independently significant factor that was inversely associated with NPC local control

  1. Electronically controllable spoof localized surface plasmons

    Science.gov (United States)

    Zhou, Yong Jin; Zhang, Chao; Yang, Liu; Xun Xiao, Qian

    2017-10-01

    Electronically controllable multipolar spoof localized surface plasmons (LSPs) are experimentally demonstrated in the microwave frequencies. It has been shown that half integer order LSPs modes exist on the corrugated ring loaded with a slit, which actually arise from the Fabry-Perot-like resonances. By mounting active components across the slit in the corrugated rings, electronic switchability and tunability of spoof LSPs modes have been accomplished. Both simulated and measured results demonstrate efficient dynamic control of the spoof LSPs. These elements may form the basis of highly integrated programmable plasmonic circuits in microwave and terahertz regimes.

  2. Model predictive Controller for Mobile Robot

    OpenAIRE

    Alireza Rezaee

    2017-01-01

    This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

  3. Dynamic Algorithm for LQGPC Predictive Control

    DEFF Research Database (Denmark)

    Hangstrup, M.; Ordys, A.W.; Grimble, M.J.

    1998-01-01

    In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated into the control......In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated...... into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive, e.g. GPS is that LQGPC enables...

  4. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  5. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  6. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  7. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  8. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  9. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

    Science.gov (United States)

    Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

    2010-07-01

    PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

  10. Intratumor microvessel density in biopsy specimens predicts local response of hypopharyngeal cancer to radiotherapy

    International Nuclear Information System (INIS)

    Zhang, Shi-Chuan; Miyamoto, Shin-ichi; Hasebe, Takahiro; Ishii, Genichiro; Ochiai, Atsushi; Kamijo, Tomoyuki; Hayashi, Ryuichi; Fukayama, Masashi

    2003-01-01

    The aim of this retrospective study was to identify reliable predictive factors for local control of hypopharyngeal cancer (HPC) treated by radiotherapy. A cohort of 38 patients with HPC treated by radical radiotherapy at the National Cancer Center Hospital East between 1992 and 1999 were selected as subjects for the present study. Paraffin-embedded pre-therapy biopsy specimens from these patients were used for immunostaining to evaluate the relationships between local tumor control and expression of the following previously reported predictive factors for local recurrence of head and neck cancer treated by radiotherapy: Ki-67, Cyclin D1, CDC25B, VEGF, p53, Bax and Bcl-2. The predictive power of microvessel density (MVD) in biopsy specimens and of clinicopathologic factors (age, gender and clinical tumor-node-metastasis stage) was also statistically analyzed. Twenty-five patients developed tumor recurrence at the primary site. Univariate analysis indicated better local control of tumors with high microvessel density [MVD≥median (39 vessels/field)] than with low MVD (< median, P=0.042). There were no significant associations between local control and expression of Ki-67 (P=0.467), Bcl-2 (P=0.127), Bax (P=0.242), p53 (P=0.262), Cyclin D1 (P=0.245), CDC25B (P=0.511) or VEGF (P=0.496). Clinicopathologic factors were also demonstrated to have no significant influence on local control (age, P=0.974; gender, P=0.372; T factor, P=0.602; N factor, P=0.530; Stage, P=0.499). MVD in biopsy specimens was closely correlated with local control of HPC treated by radiotherapy. (author)

  11. Predicting and Controlling Complex Networks

    Science.gov (United States)

    2015-06-22

    ubiquitous in nature and fundamental to evolution in ecosystems. However, a significant chal- lenge remains in understanding biodiversity since, by the...networks and control . . . . . . . . . . . . . . . . . . . 7 3.4 Pattern formation, synchronization and outbreak of biodiversity in cyclically...Ni, Y.-C. Lai, and C. Grebogi, “Pattern formation, synchronization and outbreak of biodiversity in cyclically competing games,” Physical Review E 83

  12. Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry.

    Science.gov (United States)

    Kootstra, Gert; de Boer, Bart; Schomaker, Lambert R B

    2011-03-01

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the prediction of fixations on mirror-symmetrical forms. The contrast model gives high response at the borders, whereas human observers consistently look at the symmetrical center of these forms. We propose a saliency model that predicts eye fixations using local mirror symmetry. To test the model, we performed an eye-tracking experiment with participants viewing complex photographic images and compared the data with our symmetry model and the contrast model. The results show that our symmetry model predicts human eye fixations significantly better on a wide variety of images including many that are not selected for their symmetrical content. Moreover, our results show that especially early fixations are on highly symmetrical areas of the images. We conclude that symmetry is a strong predictor of human eye fixations and that it can be used as a predictor of the order of fixation.

  13. Local control of striatal dopamine release

    Directory of Open Access Journals (Sweden)

    Roger eCachope

    2014-05-01

    Full Text Available The mesolimbic and nigrostriatal dopamine (DA systems play a key role in the physiology of reward seeking, motivation and motor control. Importantly, they are also involved in the pathophysiology of Parkinson’s and Huntington’s disease, schizophrenia and addiction. Control of DA release in the striatum is tightly linked to firing of DA neurons in the ventral tegmental area (VTA and the substantia nigra (SN. However, local influences in the striatum affect release by exerting their action directly on axon terminals. For example, endogenous glutamatergic and cholinergic activity is sufficient to trigger striatal DA release independently of cell body firing. Recent developments involving genetic manipulation, pharmacological selectivity or selective stimulation have allowed for better characterization of these phenomena. Such termino-terminal forms of control of DA release transform considerably our understanding of the mesolimbic and nigrostriatal systems, and have strong implications as potential mechanisms to modify impaired control of DA release in the diseased brain. Here, we review these and related mechanisms and their implications in the physiology of ascending DA systems.

  14. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  15. Delta-Domain Predictive Control and Identification for Control

    DEFF Research Database (Denmark)

    Lauritsen, Morten Bach

    1997-01-01

    The present thesis is concerned with different aspects of modelling, control and identification of linear systems. Traditionally, discrete-time sampled-data systems are represented using shift-operator parametrizations. Such parametrizations are not suitable at fast sampling rates. An alternative...... minimum-variance predictor as a special case and to have a well-defined continuous-time limit. By means of this new prediction method a unified framework for discrete-time and continuous-time predictive control algorithms is developed. This contains a continuous-time like discrete-time predictive...... controller which is insensitive to the choice of sampling period and has a well-defined limit in the continuous-time case. Also more conventional discrete-time predictive control methods may be described within the unified approach. The predictive control algorithms are extended to frequency weighted...

  16. Improved fuzzy PID controller design using predictive functional control structure.

    Science.gov (United States)

    Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

    2017-11-01

    In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Tracking local control of a parabolic trough collector; Control local de seguimiento cilindro parabolico ACE20

    Energy Technology Data Exchange (ETDEWEB)

    Ajona, J I; Alberdi, J; Gamero, E; Blanco, J

    1992-07-01

    In the local control, the sun position related to the trough collector is measured by two photo-resistors. The provided electronic signal is then compared with reference levels in order to get a set of B logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of o P.R.O.M. memory which is programmed with the logical equations of the control system. The memory output lines give the control command of the parabolic trough collector motor. (Author)

  18. Tracking local control of a parabolic trough collector. Control local de Seguimiento cilindro parabolico ACE 20

    Energy Technology Data Exchange (ETDEWEB)

    Ajona Maeztu, J.I.; Alberdi Primicia, J.; Gamero Aranda, E.; Blanco, J.

    1991-01-01

    In the local control, the sun position related to the trough collector is measured by two photo-resistors. the provided electronic signal is then compared with reference levels in order to get a set of 8 logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of a P.R.O.M. memory which is programmed with the logical ecuations of the control system. the memory output lines give the control commands of the parabolic trough collector motor. (author)

  19. Tracking local control of a parabolic trough collector; Control local de Seguimiento cilindro parabolico ACE 20

    Energy Technology Data Exchange (ETDEWEB)

    Ajona Maeztu, J.I.; Alberdi Primicia, J.; Gamero Aranda, E.; Blanco, J.

    1991-12-31

    In the local control, the sun position related to the trough collector is measured by two photo-resistors. the provided electronic signal is then compared with reference levels in order to get a set of 8 logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of a P.R.O.M. memory which is programmed with the logical ecuations of the control system. the memory output lines give the control commands of the parabolic trough collector motor. (author)

  20. Intelligent Predictive Control of Nonlienar Processes Using

    DEFF Research Database (Denmark)

    Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad

    1996-01-01

    This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has...... frequently been discussed in the neural network community. This paper proposes an approximate scheme, the approximate predictive control (APC), which facilitates the implementation and gives a substantial reduction in the required amount of computations. The method is based on a technique for extracting...... linear models from a nonlinear neural network and using them in designing the control system. The performance of the controller is demonstrated in a simulation study of a pneumatic servo system...

  1. Model predictive control for a thermostatic controlled system

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

    2013-01-01

    This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff temperat......This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff...

  2. Nonparametric predictive inference in statistical process control

    NARCIS (Netherlands)

    Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

    2000-01-01

    New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on

  3. Nonparametric predictive inference in statistical process control

    NARCIS (Netherlands)

    Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

    2004-01-01

    Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric

  4. State Aid, Voter Power and Local Control in Education.

    Science.gov (United States)

    Zak, Itai; Glasman, Naftaly S.

    1979-01-01

    Not only did voter power contribute meaningfully to local control behavior regardless of the exact shape of the relations between state aid and local control, but the hypothesized inverse relationship between state aid and local control did not receive support. Journal availability: see EA 511 898. (Author/IRT)

  5. Tube Model Predictive Control with an Auxiliary Sliding Mode Controller

    Directory of Open Access Journals (Sweden)

    Miodrag Spasic

    2016-07-01

    Full Text Available This paper studies Tube Model Predictive Control (MPC with a Sliding Mode Controller (SMC as an auxiliary controller. It is shown how to calculate the tube widths under SMC control, and thus how much the constraints of the nominal MPC have to be tightened in order to achieve robust stability and constraint fulfillment. The analysis avoids the assumption of infinitely fast switching in the SMC controller.

  6. [Predictive ocular motor control in Parkinson's disease].

    Science.gov (United States)

    Ying, Li; Liu, Zhen-Guo; Chen, Wei; Gan, Jing; Wang, Wen-An

    2008-02-19

    To investigate the changes of predictive ocular motor function in the patients with Parkinson's disease (PD), and to discuss its clinical value. Videonystagmography (VNG) was used to examine 24 patients with idiopathic Parkinson's disease, 15 males and 9 females, aged 61 +/- 6 (50-69), and 24 sex and age-matched healthy control subjects on random ocular saccade (with the target moving at random intervals to random positions) and predictive ocular saccade (with the 1.25-second light target moving 10 degrees right or left from the center). In the random ocular saccade program, the latency of saccade of the PD patients was 284 ms +/- 58 ms, significantly longer than that of the healthy controls (236 ms +/- 37 ms, P = 0.003). In the predictive ocular saccade pattern, the latency of saccades the PD patients was 150 ms +/- 138 ms, significantly longer than that of the healthy controls (59 ms +/- 102 ms, P = 0.002). The appearance rate of predictive saccades (with the latency of saccade <80 ms) in the PD group was 21%, significantly lower than that in the control group (31%, P = 0.003). There is dysfunction of predictive ocular motor control in the PD patients, and the cognitive function may be impaired at the early stage of PD.

  7. Prediction of localization and interactions of apoptotic proteins

    Directory of Open Access Journals (Sweden)

    Matula Pavel

    2009-07-01

    Full Text Available Abstract During apoptosis several mitochondrial proteins are released. Some of them participate in caspase-independent nuclear DNA degradation, especially apoptosis-inducing factor (AIF and endonuclease G (endoG. Another interesting protein, which was expected to act similarly as AIF due to the high sequence homology with AIF is AIF-homologous mitochondrion-associated inducer of death (AMID. We studied the structure, cellular localization, and interactions of several proteins in silico and also in cells using fluorescent microscopy. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the lipid membranes. Bioinformatic predictions were conducted to analyze the interactions of the studied proteins with each other and with other possible partners. We conducted molecular modeling of proteins with unknown 3D structures. These models were then refined by MolProbity server and employed in molecular docking simulations of interactions. Our results show data acquired using a combination of modern in silico methods and image analysis to understand the localization, interactions and functions of proteins AMID, AIF, endonuclease G, and other apoptosis-related proteins.

  8. General predictive control using the delta operator

    DEFF Research Database (Denmark)

    Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad; Ravn, Ole

    1993-01-01

    This paper deals with two-discrete-time operators, the conventional forward shift-operator and the δ-operator. Both operators are treated in view of construction of suitable solutions to the Diophantine equation for the purpose of prediction. A general step-recursive scheme is presented. Finally...... a general predictive control (GPC) is formulated and applied adaptively to a continuous-time plant...

  9. Nonlinear predictive control in the LHC accelerator

    CERN Document Server

    Blanco, E; Cristea, S; Casas, J

    2009-01-01

    This paper describes the application of a nonlinear model-based control strategy in a real challenging process. A predictive controller based on a nonlinear model derived from physical relationships, mainly heat and mass balances, has been developed and commissioned in the inner triplet heat exchanger unit (IT-HXTU) of the large hadron collider (LHC) particle accelerator at European Center for Nuclear Research (CERN). The advanced regulation\\ maintains the magnets temperature at about 1.9 K. The development includes a constrained nonlinear state estimator with a receding horizon estimation procedure to improve the regulator predictions.

  10. Using fire-weather forecasts and local weather observations in predicting burning index for individual fire-danger stations.

    Science.gov (United States)

    Owen P. Cramer

    1958-01-01

    Any agency engaged in forest-fire control needs accurate weather forecasts and systematic procedures for making the best use of predicted and reported weather information. This study explores the practicability of using several tabular and graphical aids for converting area forecasts and local observations of relative humidity and wind speed into predicted values for...

  11. Towards structural controllability of local-world networks

    International Nuclear Information System (INIS)

    Sun, Shiwen; Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi

    2016-01-01

    Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

  12. Towards structural controllability of local-world networks

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Shiwen, E-mail: sunsw80@126.com [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China); Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China)

    2016-05-20

    Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

  13. Applying model predictive control to power system frequency control

    OpenAIRE

    Ersdal, AM; Imsland, L; Cecilio, IM; Fabozzi, D; Thornhill, NF

    2013-01-01

    16.07.14 KB Ok to add accepted version to Spiral Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) cont...

  14. Model Predictive Control for Integrating Traffic Control Measures

    NARCIS (Netherlands)

    Hegyi, A.

    2004-01-01

    Dynamic traffic control measures, such as ramp metering and dynamic speed limits, can be used to better utilize the available road capacity. Due to the increasing traffic volumes and the increasing number of traffic jams the interaction between the control measures has increased such that local

  15. Prediction of resource volumes at untested locations using simple local prediction models

    Science.gov (United States)

    Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

    2006-01-01

    This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

  16. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  17. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2011-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  18. Quantized Predictive Control over Erasure Channels

    DEFF Research Database (Denmark)

    E. Quevedo, Daniel; Østergaard, Jan

    2009-01-01

    .i.d. dropouts, the controller transmits data packets containing quantized plant input predictions. These minimize a finite horizon cost function and are provided by an appropriate optimal entropy coded dithered lattice vector quantizer. Within this context, we derive an equivalent noise-shaping model...

  19. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  20. Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Yang Xiaoke

    2015-03-01

    Full Text Available Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.

  1. Plant control using embedded predictive models

    International Nuclear Information System (INIS)

    Godbole, S.S.; Gabler, W.E.; Eschbach, S.L.

    1990-01-01

    B and W recently undertook the design of an advanced light water reactor control system. A concept new to nuclear steam system (NSS) control was developed. The concept, which is called the Predictor-Corrector, uses mathematical models of portions of the controlled NSS to calculate, at various levels within the system, demand and control element position signals necessary to satisfy electrical demand. The models give the control system the ability to reduce overcooling and undercooling of the reactor coolant system during transients and upsets. Two types of mathematical models were developed for use in designing and testing the control system. One model was a conventional, comprehensive NSS model that responds to control system outputs and calculates the resultant changes in plant variables that are then used as inputs to the control system. Two other models, embedded in the control system, were less conventional, inverse models. These models accept as inputs plant variables, equipment states, and demand signals and predict plant operating conditions and control element states that will satisfy the demands. This paper reports preliminary results of closed-loop Reactor Coolant (RC) pump trip and normal load reduction testing of the advanced concept. Results of additional transient testing, and of open and closed loop stability analyses will be reported as they are available

  2. Local environmental quality positively predicts breastfeeding in the UK's Millennium Cohort Study.

    Science.gov (United States)

    Brown, Laura J; Sear, Rebecca

    2017-01-01

    Background and Objectives: Breastfeeding is an important form of parental investment with clear health benefits. Despite this, rates remain low in the UK; understanding variation can therefore help improve interventions. Life history theory suggests that environmental quality may pattern maternal investment, including breastfeeding. We analyse a nationally representative dataset to test two predictions: (i) higher local environmental quality predicts higher likelihood of breastfeeding initiation and longer duration; (ii) higher socioeconomic status (SES) provides a buffer against the adverse influences of low local environmental quality. Methodology: We ran factor analysis on a wide range of local-level environmental variables. Two summary measures of local environmental quality were generated by this analysis-one 'objective' (based on an independent assessor's neighbourhood scores) and one 'subjective' (based on respondent's scores). We used mixed-effects regression techniques to test our hypotheses. Results: Higher objective, but not subjective, local environmental quality predicts higher likelihood of starting and maintaining breastfeeding over and above individual SES and area-level measures of environmental quality. Higher individual SES is protective, with women from high-income households having relatively high breastfeeding initiation rates and those with high status jobs being more likely to maintain breastfeeding, even in poor environmental conditions. Conclusions and Implications: Environmental quality is often vaguely measured; here we present a thorough investigation of environmental quality at the local level, controlling for individual- and area-level measures. Our findings support a shift in focus away from individual factors and towards altering the landscape of women's decision making contexts when considering behaviours relevant to public health.

  3. Upgrading the Fermilab Linac local control system

    International Nuclear Information System (INIS)

    McCrory, E.S.; Goodwin, R.W.; Shea, M.F.

    1991-02-01

    A new control system for the Fermilab Linac is being designed, built and implemented. First, the nine-year-old linac control system is being replaced. Second, a control system for the new 805 MHz part of the linac is being built. The two systems are essentially identical, so that when the installations are complete, we will still have a single Linac Control System. 8 refs., 5 figs

  4. Hearing aid controlled by binaural source localizer

    NARCIS (Netherlands)

    2009-01-01

    An adaptive directional hearing aid system comprising a left hearing aid and a right hearing aid, wherein a binaural acoustic source localizer is located in the left hearing aid or in the right hearing aid or in a separate body- worn device connected wirelessly to the left hearing aid and the right

  5. Deciding the Fate of Local Control.

    Science.gov (United States)

    Schlechty, Phillip C.

    1992-01-01

    The fundamental job of school board members is to view themselves as moral and cultural leaders and to transform the needs of groups to a higher and more noble framework. Lists the National School Boards Association's statement on the governance role of the local school board. (MLF)

  6. Electrochemotherapy increases local control after incomplete ...

    African Journals Online (AJOL)

    ... horse with electrochemotherapy (ECT) using cisplatin as chemotherapy agent. Two sessions of ECT were performed at two-week intervals using local cisplatin followed by trains of biphasic electric pulses applied using different electrodes until complete coverage of the area was achieved. The treatment was well tolerated ...

  7. Predictive access control for distributed computation

    DEFF Research Database (Denmark)

    Yang, Fan; Hankin, Chris; Nielson, Flemming

    2013-01-01

    We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive access control policies — policies based on the future beh...... behavior of a program. A novel feature of our approach is that we can define policies concerning secondary use of data....

  8. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  9. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    SILVA R. G.

    1999-01-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  10. Enhancing the Situational Awareness of Airfield Local Controllers

    National Research Council Canada - National Science Library

    Mowery, Samuel

    2002-01-01

    .... In air traffic control operations, situational awareness of a local controller at an airfield such as Marine Corps Air Station Camp Pendleton, California, is critical to prevention of catastrophic...

  11. Wind farms production: Control and prediction

    Science.gov (United States)

    El-Fouly, Tarek Hussein Mostafa

    Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect

  12. Topography printing to locally control wettability.

    Science.gov (United States)

    Zheng, Zijian; Azzaroni, Omar; Zhou, Feng; Huck, Wilhelm T S

    2006-06-21

    This paper reports a new patterning method, which utilizes NaOH to facilitate the irreversible binding between the PDMS stamp and substrates and subsequent cohesive mechanical failure to transfer the PDMS patterns. Our method shows high substrate tolerance and can be used to "print" various PDMS geometries on a wide range of surfaces, including Si100, glass, gold, polymers, and patterned SU8 photoresist. Using this technique, we are able to locally change the wettability of substrate surfaces by printing well-defined PDMS architectures on the patterned SU8 photoresist. It is possible to generate differential wetting and dewetting properties in microchannels and in the PDMS printed area, respectively.

  13. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  14. Towards probabilistic synchronisation of local controllers

    Czech Academy of Sciences Publication Activity Database

    Herzallah, R.; Kárný, Miroslav

    2017-01-01

    Roč. 48, č. 3 (2017), s. 604-615 ISSN 0020-7721 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : cooperative control * optimal control * complex system s * stochastic system s * fully probabilistic desing Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 2.285, year: 2016

  15. Short-term prediction of local wind conditions

    DEFF Research Database (Denmark)

    Landberg, L.

    2001-01-01

    This paper will describe a system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual...

  16. Edge localized modes control: experiment and theory

    International Nuclear Information System (INIS)

    Becoulet, M.; Huysmans, G.; Thomas, P.; Joffrin, E.; Rimini, F.; Monier-Garbet, P.; Grosman, A.; Ghendrih, P.; Parail, V.; Lomas, P.; Matthews, G.; Wilson, H.; Gryaznevich, M.; Counsell, G.; Loarte, A.; Saibene, G.; Sartori, R.; Leonard, A.; Snyder, P.; Evans, T.; Gohil, P.; Moyer, R.; Kamada, Y.; Oyama, N.; Hatae, T.; Kamiya, K.; Degeling, A.; Martin, Y.; Lister, J.; Rapp, J.; Perez, C.; Lang, P.; Chankin, A; Eich, T.; Sips, A.; Stober, J.; Horton, L.; Kallenbach, A.; Suttrop, W.; Saarelma, S.; Cowley, S.; Loennroth, J.; Shimada, M.; Polevoi, A.; Federici, G.

    2005-01-01

    The paper reviews recent theoretical and experimental results focussing on the identification of the key factors controlling ELM energy and particle losses both in natural ELMs and in the presence of external controlling mechanisms. Present experiment and theory pointed out the benefit of the high plasma shaping, high q 95 and high pedestal density in reducing the ELM affected area and conductive energy losses in Type I ELMs. Small benign ELMs regimes in present machines (EDA, HRS, Type II, Grassy, QH, Type III in impurity seeded discharges at high δ ) and their relevance for ITER are reviewed. Recent studies of active control of ELMs using stochastic boundaries, small pellets and edge current generation are presented

  17. Electro-statically controllable graphene local heater

    Science.gov (United States)

    Wang, Hui-Shan; Deng, Lian-Wen; Li, Lei; Sun, Qiu-Juan; Xie, Hong; Wang, Hao-Min

    2018-03-01

    We report on current-induced thermal power investigation of graphene nanostructure for potential local-heating applications. It is found that the efficiency of heating can be greatly improved if graphene is patterned into structures with narrow width and long channel. In a narrow graphene-ribbon, the Joule heating power exhibits an obvious dependence on the back-gate voltage. By monitoring Raman spectra, the temperature of graphene-ribbon can be determined. The temperature of graphene-ribbon is modulated by the electric field effect when the sample is sourced with a relatively high current. Project supported by the National Key R&D Program of China (Grant No. 2017YFF0206106), the Chinese Academy of Sciences (Grant No. XDB04040300), the National Natural Science Foundation of China (Grant No. 51772317), and the Science and Technology Commission of Shanghai Municipality, China (Grant No. 16ZR1442700).

  18. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

    2015-01-01

    We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....

  19. Globalization and Localization of the Management Control System package

    DEFF Research Database (Denmark)

    Toldbod, Thomas; Israelsen, Poul

    2015-01-01

    Through an empirical case study, this article examines the operation of multiple management control systems as a package in a Danish manufacturing company. The analysis focuses on four different management control systems – cybernetic controls, planning controls, reward controls, and administrative...... the organization and others have more particular characteristics. Specifically, this study finds that cybernetic controls and administrative controls are designed as global management control systems. Planning controls and reward and compensation controls are glocal systems. The finding leads to the conclusion...... controls – through the theoretical lens of globalization, localization, and glocalization. Based on a single-case study, the analysis documents that these different management control systems are affected differently by the processes of globalization and localization, some of which are universal throughout...

  20. Optimization control of LNG regasification plant using Model Predictive Control

    Science.gov (United States)

    Wahid, A.; Adicandra, F. F.

    2018-03-01

    Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

  1. Controlling spatio-temporal extreme events by decreasing the localized energy

    International Nuclear Information System (INIS)

    Du Lin; Xu Wei; Li Zhanguo; Zhou Bingchang

    2011-01-01

    The problem of controlling extreme events in spatially extended dynamical systems is investigated in this Letter. Based on observations of the system state, the control technique we proposed locally decreases the spatial energy of the amplitude in the vicinity of the highest burst, without needs of any knowledge or prediction of the system model. Considering the specific Complex Ginzburg-Landau equation, we provide theoretical analysis for designing the localized state feedback controller. More exactly, a simple control law by varying a damping parameter at control region is chose to achieve the control. Numerical simulations and statistic analysis demonstrate that extreme events can be efficiently suppressed by our strategy. In particular, the cost of the control and the tolerant time delay in applying the control is considered in detail. - Highlights: → We propose a local control scheme to suppress spatio-temporal extreme events. → The control is address by decreasing the spatial energy of the system locally. → The detail control law is to apply localized state feedback based on observations. → The cost of the control increases with the size of the control region exponentially. → The tolerant delay of the control is about 5-6 times of lifetime of extreme events.

  2. Nowcast Predictions for Local Transmission of Chikungunya Virus

    Data.gov (United States)

    U.S. Department of Health & Human Services — Interactive visualization: http://www.cdc.gov/chikungunya/modeling/index.html. This dataset contains monthly predictions for the spread of chikungunya virus...

  3. Predictive torque and flux control of an induction machine drive ...

    Indian Academy of Sciences (India)

    Finite-state model predictive control; fuzzy decision making; multi-objective optimization; predictive torque control. Abstract. Among the numerous direct torque control techniques, the finite-state predictive torque control (FS-PTC) has emerged as a powerful alternative as it offers the fast dynamic response and the flexibility to ...

  4. Enabling Controlling Complex Networks with Local Topological Information.

    Science.gov (United States)

    Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

    2018-03-15

    Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

  5. Climate Controls AM Fungal Distributions from Global to Local Scales

    Science.gov (United States)

    Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

    2016-12-01

    Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal

  6. Prediction of critical heat flux by a new local condition hypothesis

    International Nuclear Information System (INIS)

    Im, J. H.; Jun, K. D.; Sim, J. W.; Deng, Zhijian

    1998-01-01

    Critical Heat Flux(CHF) was predicted for uniformly heated vertical round tube by a new local condition hypothesis which incorporates a local true steam quality. This model successfully overcame the difficulties in predicted the subcooled and quality CHF by the thermodynamic equilibrium quality. The local true steam quality is a dependent variable of the thermodynamic equilibrium quality at the exit and the quality at the Onset of Significant Vaporization(OSV). The exit thermodynamic equilibrium quality was obtained from the heat balance, and the quality at OSV was obtained from the Saha-Zuber correlation. In the past CHF has been predicted by the experimental correlation based on local or non-local condition hypothesis. This preliminary study showed that all the available world data on uniform CHF could be predicted by the model based on the local condition hypothesis

  7. Error Control in Distributed Node Self-Localization

    Directory of Open Access Journals (Sweden)

    Ying Zhang

    2008-03-01

    Full Text Available Location information of nodes in an ad hoc sensor network is essential to many tasks such as routing, cooperative sensing, and service delivery. Distributed node self-localization is lightweight and requires little communication overhead, but often suffers from the adverse effects of error propagation. Unlike other localization papers which focus on designing elaborate localization algorithms, this paper takes a different perspective, focusing on the error propagation problem, addressing questions such as where localization error comes from and how it propagates from node to node. To prevent error from propagating and accumulating, we develop an error-control mechanism based on characterization of node uncertainties and discrimination between neighboring nodes. The error-control mechanism uses only local knowledge and is fully decentralized. Simulation results have shown that the active selection strategy significantly mitigates the effect of error propagation for both range and directional sensors. It greatly improves localization accuracy and robustness.

  8. QUESTION OF IMPROVEMENT OF BUDGET CONTROL AT THE LOCAL LEVEL

    Directory of Open Access Journals (Sweden)

    Oleg Vatslavskyi

    2016-11-01

    Full Text Available The aim is to analyse the current practice of budgetary control to develop its areas of improvement at the local level. The subject of the research is theoretical and methodological principles of functioning of budgetary control at the local level. The methodological basis of the study comprises research approaches, general theoretical principles of scientific knowledge, system of methods and techniques. The paper clarifies the nature of budgetary control at the local level. The main bodies that implement budget control, namely the State Audit Office, the Accounting Chamber, the State Treasury, the State Fiscal Service, financial and management departments are singled out. It is found that the leading part among all of the special budgetary control bodies in the rational and efficient use of local financial resources is performed by the State Audit Office. Analysis of the State Audit Office in three regions of Ukraine for the period 2013-2015 has been carried out. We distinguish two main types of violations that the State Audit Service reveals during its work at the local level: 1 shortfall in the financial resources of public enterprises, institutions and organizations; 2 violations that lead to illegal, non-target costs and shortages. It is proved that the efficiency of budgetary control is low. The paper states basic problems of budget control at the local level, namely, low income funds and reimbursements from violations revealed by regulatory agencies; insufficient work with the public to explain the problems of budget control and eliminate violations in the public sector; lack of a consolidated legal act, which would have regulated all the major components of budgetary control; insufficient use of controlling and auditing methods aimed at determining the effectiveness of budget funds; low preventive function on the part of budget control bodies. We offer ways to improve budget control at the local level through: standardization system of

  9. Online prediction and control in nonlinear stochastic systems

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov

    2002-01-01

    speed and the relationship between (primarily) wind speed and wind power (the power curve). In paper G the model parameters are estimated using a RLS algorithm and any systematic time-variation of the model parameters is disregarded. Two di erent parameterizations of the power curve is considered...... are estimated using the algorithm proposed in paper C. The power curve and the diurnal variation of wind speed is estimated separately using the local polynomial regression procedure described in paper A . In paper J the parameters of the prediction model is assumed to be smooth functions of wind direction (and......The present thesis consists of a summary report and ten research papers. The subject of the thesis is on-line prediction and control of non-linear and non-stationary systems based on stochastic modelling. The thesis consists of three parts where the rst part deals with on-line estimation in linear...

  10. A mobile console for local access to accelerator control systems.

    CERN Multimedia

    1981-01-01

    Microprocessors were installed as auxiliary crate controllers (ACCs) in the CAMAC interface of control systems for various accelerators. The same ACC was also at the hearth of a stand-alone system in the form of a mobile console. This was also used for local access to the control systems for tests and development work (Annual Report 1981, p. 80, Fig. 10).

  11. Local hierarchical control for industrial microgrids with improved frequency regulation

    DEFF Research Database (Denmark)

    Rey, Juan M.; Vergara, Pedro P.; Castilla, Miguel

    2018-01-01

    Local control strategies that operate without relying on communication systems enhance flexibility and reliability of AC industrial microgrids. Based on a previous work in which a secondary switched control was proposed, this paper presents a complementary strategy to improve the frequency......-use of communications. Experimental results obtained on a laboratory microgrid are presented to validate the performance of the proposed complementary control strategy....

  12. Predicting Subcellular Localization of Proteins by Bioinformatic Algorithms

    DEFF Research Database (Denmark)

    Nielsen, Henrik

    2015-01-01

    was used. Various statistical and machine learning algorithms are used with all three approaches, and various measures and standards are employed when reporting the performances of the developed methods. This chapter presents a number of available methods for prediction of sorting signals and subcellular...

  13. Local dimension and finite time prediction in coupled map lattices

    Indian Academy of Sciences (India)

    In most of the cases these systems often exhibit highly complex type of ... tical applications bred vectors are different in two aspects. Firstly, for bred .... prediction 〈y| x〉 using the conditional distribution obtained from the joint distri- bution p(y, x) ...

  14. Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry

    NARCIS (Netherlands)

    Kootstra, Geert; de Boer, Bart; Schomaker, Lambertus

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the

  15. Predicting eye fixations on complex visual stimuli using local symmetry

    NARCIS (Netherlands)

    Kootstra, G.; de Boer, B.; Schomaker, L.R.B.

    2011-01-01

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the

  16. Blockage-induced condensation controlled by a local reaction

    Science.gov (United States)

    Cirillo, Emilio N. M.; Colangeli, Matteo; Muntean, Adrian

    2016-10-01

    We consider the setup of stationary zero range models and discuss the onset of condensation induced by a local blockage on the lattice. We show that the introduction of a local feedback on the hopping rates allows us to control the particle fraction in the condensed phase. This phenomenon results in a current versus blockage parameter curve characterized by two nonanalyticity points.

  17. Validation of the mortality prediction equation for damage control ...

    African Journals Online (AJOL)

    , preoperative lowest pH and lowest core body temperature to derive an equation for the purpose of predicting mortality in damage control surgery. It was shown to reliably predict death despite damage control surgery. The equation derivation ...

  18. STAR-TYPE LOCAL AREA NETWORK ACCESS CONTROL

    Institute of Scientific and Technical Information of China (English)

    逯昭义; 齐藤忠夫

    1990-01-01

    The multiple access fashion is a new resolution for the star-type local area network (LAN) access control and star-type optical fibre LAN. Arguments about this network are discussed, and the results are introduced.

  19. Traditional methods of social control in Afikpo north local ...

    African Journals Online (AJOL)

    Traditional methods of social control in Afikpo north local government area, Ebonyi state south eastern Nigeria. ... Journal of Religion and Human Relations ... simple percentage was used in presenting and interpreting the quantitative data.

  20. Data Driven Economic Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Masoud Kheradmandi

    2018-04-01

    Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

  1. Experimental Validation of Energy Resources Integration in Microgrids via Distributed Predictive Control

    DEFF Research Database (Denmark)

    Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso; Marinelli, Mattia

    2014-01-01

    This paper presents an innovative control scheme for the management of energy consumption in commercial build- ings with local energy production, such as photovoltaic panels or wind turbine and an energy storage unit. The presented scheme is based on distributed model predictive controllers, which...... sources, a vanadium redox battery system, resistive load, and a point of common coupling to the national grid. Several experiments are carried to assess the performance of the control scheme in managing local energy pro- duction and consumption....

  2. Prediction of local effects of proposed cooling ponds

    International Nuclear Information System (INIS)

    Hicks, B.B.

    1978-01-01

    A Fog Excess Water (FEW) Index has been shown to provide a good measure of the likelihood for steam fog to occur at specific cooling pond installations. The FEW Index is derived from the assumption that the surface boundary layer over a cooling pond will be strongly convective, and that highly efficient vertical transport mechanisms will result in a thorough mixing of air saturated at surface temperature with ambient air aloft. Available data support this assumption. An extension of this approach can be used to derive a simple indicator for use in predicting the formation of rime ice in the immediate downwind environs of a cooling pond. In this case, it is supposed that rime ice will be deposited whenever steam fog and sub-freezing surface temperatures are predicted. This provides a convenient method for interpreting pre-existing meteorological information in order to assess possible icing effects while in the early design stages of the planning process. However, it remains necessary to derive accurate predictions of the cooling pond water surface temperature. Once a suitable and proven procedure for this purpose has been demonstrated, it is then a simple matter to employ the FEW Index in evaluations of the relative merits of alternative cooling pond designs, with the purpose of minimizing overall environmental impact

  3. Adjuvant radiation for vulvar carcinoma: improved local control

    International Nuclear Information System (INIS)

    Faul, Clare M.; Mirmow, Dwight; Huang Qingshon; Gerszten, Kristina; Day, Roger; Jones, Mirka W.

    1997-01-01

    Purpose: Local recurrence is a significant problem following primary surgery for advanced vulva carcinoma. The objectives of this study were to evaluate the impact of adjuvant vulvar radiation on local control in high risk patients and the impact of local recurrence on overall survival. Methods and Materials: From 1980-1994, 62 patients with invasive vulva carcinoma and either positive or close (less 8 mm) margins of excision were retrospectively studied. Thirty-one patients were treated with adjuvant radiation therapy to the vulva and 31 patients were observed after surgery. Kaplan-Meier estimates and the Cox proportional hazard regression model were used to evaluate the effect of adjuvant radiation therapy on local recurrence and overall survival. Independent prognostic factors for local recurrence and survival were also assessed. Results: Local recurrence occurred in 58% of observed patients and 16% in patients treated with adjuvant radiation therapy. Adjuvant radiation therapy significantly reduced local recurrence rates in both the close margin and positive margin groups (p = 0.036, p = 0.0048). On both univariate and multivariate analysis adjuvant radiation and margins of excision were significant prognostic predictors for local control. Significant determinants of actuarial survival included International Federation of Gynecologists and Obstetricians (FIGO) stage, percentage of pathologically positive inguinal nodes and margins of excision. The positive margin observed group had a significantly poorer actuarial 5 year survival than the other groups (p = 0.0016) and adjuvant radiation significantly improved survival for this group. The 2 year actuarial survival after developing local recurrence was 25%. Local recurrence was a significant predictor for death from vulva carcinoma (risk ratio 3.54). Conclusion: Local recurrence is a common occurrence in high risk patients. In this study adjuvant radiation therapy significantly reduced local recurrence rates and

  4. B220 analysis with the local lymph node assay: proposal for a more flexible prediction model.

    Science.gov (United States)

    Betts, Catherine J; Dearman, Rebecca J; Kimber, Ian; Ryan, Cindy A; Gerberick, G Frank; Lalko, Jon; Api, Anne Marie

    2007-01-01

    The mouse local lymph node assay (LLNA) has been developed and validated for the identification of chemicals that have the potential to induce skin sensitisation. In common with other predictive test methods the accuracy of the LLNA is not absolute and experience has revealed that a few chemicals, including for instance a minority of skin irritants, may elicit false-positive reactions in the assay. To improve further the performance of the LLNA, and to eliminate or reduce false-positives, there has been interest in an adjunct method in which the ability of chemicals to cause increases in the frequency of B220(+) lymphocytes in skin-draining lymph nodes is measured. Previous studies suggest that the use of B220 analyses aligned with the standard LLNA may serve to distinguish further between contact allergens and skin irritants. In the original predictive model, chemicals were regarded as being skin sensitisers if they were able to induce a 1.25-fold or greater increase in the percentage of B220(+) cells within lymph nodes compared with concurrent vehicle controls. Although this first prediction model has proven useful, in the light of more recent experience, and specifically as a consequence of some variability observed in the frequency of B220(+) lymphocytes in nodes taken from vehicle control-treated animals, it is timely now to reconsider and refine the model. As a result a new prediction model is proposed in which reliance on the use of absolute thresholds is reduced, and in which small changes in control values can be better accommodated. (c) 2007 John Wiley & Sons, Ltd.

  5. Local control of Ewing's sarcoma: an analysis of 67 patients

    International Nuclear Information System (INIS)

    Brown, A.P.; Fixsen, J.A.; Plowman, P.N.

    1987-01-01

    Local control of Ewing's sarcoma was analysed in a series of 67 patients treated by surgery and/or radiotherapy as well as combination chemotherapy. Radiotherapy was employed with or without surgery in 60 patients and produced an overall local control rate of 55%; complete excision of the primary lesion seemed to be beneficial. There was a marked variation in control rates depending on the site of the primary lesion: limb 85%, rib 53%, pelvis 31% and other sites 33%.Primary tumours greater than 10 cm in diameter were significantly less likely to be controlled. Using daily fractions of approximately 180 cGy, total doses in excess of 6000 cGy seem more likely to produce serious late morbidity amd may not increase the local control rate. No cases of second malignancy arising in irradiated tissue have been observed to date, but one patient developed acute lymphoblastic leukaemia. (author)

  6. Predicting the subcellular localization of viral proteins within a mammalian host cell

    Directory of Open Access Journals (Sweden)

    Thomas DY

    2006-04-01

    Full Text Available Abstract Background The bioinformatic prediction of protein subcellular localization has been extensively studied for prokaryotic and eukaryotic organisms. However, this is not the case for viruses whose proteins are often involved in extensive interactions at various subcellular localizations with host proteins. Results Here, we investigate the extent of utilization of human cellular localization mechanisms by viral proteins and we demonstrate that appropriate eukaryotic subcellular localization predictors can be used to predict viral protein localization within the host cell. Conclusion Such predictions provide a method to rapidly annotate viral proteomes with subcellular localization information. They are likely to have widespread applications both in the study of the functions of viral proteins in the host cell and in the design of antiviral drugs.

  7. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  8. Spontaneous local alpha oscillations predict motion-induced blindness.

    Science.gov (United States)

    Händel, Barbara F; Jensen, Ole

    2014-11-01

    Bistable visual illusions are well suited for exploring the neuronal states of the brain underlying changes in perception. In this study, we investigated oscillatory activity associated with 'motion-induced blindness' (MIB), which denotes the perceptual disappearance of salient target stimuli when a moving pattern is superimposed on them (Bonneh et al., ). We applied an MIB paradigm in which illusory target disappearances would occur independently in the left and right hemifields. Both illusory and real target disappearance were followed by an alpha lateralization with weaker contralateral than ipsilateral alpha activity (~10 Hz). However, only the illusion showed early alpha lateralization in the opposite direction, which preceded the alpha effect present for both conditions and coincided with the estimated onset of the illusion. The duration of the illusory disappearance was further predicted by the magnitude of this early lateralization when considered over subjects. In the gamma band (60-80 Hz), we found an increase in activity contralateral relative to ipsilateral only after a real disappearance. Whereas early alpha activity was predictive of onset and length of the illusory percept, gamma activity showed no modulation in relation to the illusion. Our study demonstrates that the spontaneous changes in visual alpha activity have perceptual consequences. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  9. Predictive Control of Networked Multiagent Systems via Cloud Computing.

    Science.gov (United States)

    Liu, Guo-Ping

    2017-01-18

    This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

  10. An ensemble method for predicting subnuclear localizations from primary protein structures.

    Directory of Open Access Journals (Sweden)

    Guo Sheng Han

    Full Text Available BACKGROUND: Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. METHODOLOGY/PRINCIPAL FINDINGS: A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. CONCLUSIONS: It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method

  11. MU-LOC: A Machine-Learning Method for Predicting Mitochondrially Localized Proteins in Plants

    DEFF Research Database (Denmark)

    Zhang, Ning; Rao, R Shyama Prasad; Salvato, Fernanda

    2018-01-01

    -sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently......, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale prediction of plant mitochondrial proteins. We collected a comprehensive dataset of plant subcellular localization, extracted features including amino...

  12. Predicting Loss-of-Control Boundaries Toward a Piloting Aid

    Science.gov (United States)

    Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

  13. Real-time prediction of respiratory motion based on local regression methods

    International Nuclear Information System (INIS)

    Ruan, D; Fessler, J A; Balter, J M

    2007-01-01

    Recent developments in modulation techniques enable conformal delivery of radiation doses to small, localized target volumes. One of the challenges in using these techniques is real-time tracking and predicting target motion, which is necessary to accommodate system latencies. For image-guided-radiotherapy systems, it is also desirable to minimize sampling rates to reduce imaging dose. This study focuses on predicting respiratory motion, which can significantly affect lung tumours. Predicting respiratory motion in real-time is challenging, due to the complexity of breathing patterns and the many sources of variability. We propose a prediction method based on local regression. There are three major ingredients of this approach: (1) forming an augmented state space to capture system dynamics, (2) local regression in the augmented space to train the predictor from previous observation data using semi-periodicity of respiratory motion, (3) local weighting adjustment to incorporate fading temporal correlations. To evaluate prediction accuracy, we computed the root mean square error between predicted tumor motion and its observed location for ten patients. For comparison, we also investigated commonly used predictive methods, namely linear prediction, neural networks and Kalman filtering to the same data. The proposed method reduced the prediction error for all imaging rates and latency lengths, particularly for long prediction lengths

  14. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

    Directory of Open Access Journals (Sweden)

    Kohlbacher Oliver

    2009-09-01

    Full Text Available Abstract Background Knowledge of subcellular localization of proteins is crucial to proteomics, drug target discovery and systems biology since localization and biological function are highly correlated. In recent years, numerous computational prediction methods have been developed. Nevertheless, there is still a need for prediction methods that show more robustness and higher accuracy. Results We extended our previous MultiLoc predictor by incorporating phylogenetic profiles and Gene Ontology terms. Two different datasets were used for training the system, resulting in two versions of this high-accuracy prediction method. One version is specialized for globular proteins and predicts up to five localizations, whereas a second version covers all eleven main eukaryotic subcellular localizations. In a benchmark study with five localizations, MultiLoc2 performs considerably better than other methods for animal and plant proteins and comparably for fungal proteins. Furthermore, MultiLoc2 performs clearly better when using a second dataset that extends the benchmark study to all eleven main eukaryotic subcellular localizations. Conclusion MultiLoc2 is an extensive high-performance subcellular protein localization prediction system. By incorporating phylogenetic profiles and Gene Ontology terms MultiLoc2 yields higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. MultiLoc2 is available as user-friendly and free web-service, available at: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc2.

  15. Nonlinear Model Predictive Control for Cooperative Control and Estimation

    Science.gov (United States)

    Ru, Pengkai

    Recent advances in computational power have made it possible to do expensive online computations for control systems. It is becoming more realistic to perform computationally intensive optimization schemes online on systems that are not intrinsically stable and/or have very small time constants. Being one of the most important optimization based control approaches, model predictive control (MPC) has attracted a lot of interest from the research community due to its natural ability to incorporate constraints into its control formulation. Linear MPC has been well researched and its stability can be guaranteed in the majority of its application scenarios. However, one issue that still remains with linear MPC is that it completely ignores the system's inherent nonlinearities thus giving a sub-optimal solution. On the other hand, if achievable, nonlinear MPC, would naturally yield a globally optimal solution and take into account all the innate nonlinear characteristics. While an exact solution to a nonlinear MPC problem remains extremely computationally intensive, if not impossible, one might wonder if there is a middle ground between the two. We tried to strike a balance in this dissertation by employing a state representation technique, namely, the state dependent coefficient (SDC) representation. This new technique would render an improved performance in terms of optimality compared to linear MPC while still keeping the problem tractable. In fact, the computational power required is bounded only by a constant factor of the completely linearized MPC. The purpose of this research is to provide a theoretical framework for the design of a specific kind of nonlinear MPC controller and its extension into a general cooperative scheme. The controller is designed and implemented on quadcopter systems.

  16. Notions of local controllability and optimal feedforward control for quantum systems

    International Nuclear Information System (INIS)

    Chakrabarti, Raj

    2011-01-01

    Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

  17. Notions of local controllability and optimal feedforward control for quantum systems

    Energy Technology Data Exchange (ETDEWEB)

    Chakrabarti, Raj, E-mail: rchakra@purdue.edu [School of Chemical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

    2011-05-06

    Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

  18. Combining local and global optimisation for virtual camera control

    OpenAIRE

    Burelli, Paolo; Yannakakis, Georgios N.; 2010 IEEE Symposium on Computational Intelligence and Games

    2010-01-01

    Controlling a virtual camera in 3D computer games is a complex task. The camera is required to react to dynamically changing environments and produce high quality visual results and smooth animations. This paper proposes an approach that combines local and global search to solve the virtual camera control problem. The automatic camera control problem is described and it is decomposed into sub-problems; then a hierarchical architecture that solves each sub-problem using the most appropriate op...

  19. Failure to Achieve a PSA Level ≤1 ng/mL After Neoadjuvant LHRHA Therapy Predicts for Lower Biochemical Control Rate and Overall Survival in Localized Prostate Cancer Treated With Radiotherapy

    International Nuclear Information System (INIS)

    Mitchell, Darren M.; McAleese, Jonathan; Park, Richard M.; Stewart, David P.; Stranex, Stephen; Eakin, Ruth L.; Houston, Russell F.; O'Sullivan, Joe M.

    2007-01-01

    Purpose: To investigate whether failure to suppress the prostate-specific antigen (PSA) level to ≤1 ng/mL after ≥2 months of neoadjuvant luteinizing hormone-releasing hormone agonist therapy in patients scheduled to undergo external beam radiotherapy for localized prostate carcinoma is associated with reduced biochemical failure-free survival. Methods and Materials: A retrospective case note review of consecutive patients with intermediate- or high-risk localized prostate cancer treated between January 2001 and December 2002 with neoadjuvant hormonal deprivation therapy, followed by concurrent hormonal therapy and radiotherapy was performed. Patient data were divided for analysis according to whether the PSA level in Week 1 of radiotherapy was ≤1.0 ng/mL. Biochemical failure was determined using the American Society for Therapeutic Radiology and Oncology (Phoenix) definition. Results: A total of 119 patients were identified. The PSA level after neoadjuvant hormonal deprivation therapy was ≤1 ng/mL in 67 patients and >1 ng/mL in 52. At a median follow-up of 49 months, the 4-year actuarial biochemical failure-free survival rate was 84% vs. 60% (p = 0.0016) in favor of the patients with a PSA level after neoadjuvant hormonal deprivation therapy of ≤1 ng/mL. The overall survival rate was 94% vs. 77.5% (p = 0.0045), and the disease-specific survival rate at 4 years was 98.5% vs. 82.5%. Conclusions: The results of our study have shown that patients with a PSA level >1 ng/mL at the beginning of external beam radiotherapy after ≥2 months of neoadjuvant luteinizing hormone-releasing hormone agonist therapy have a significantly greater rate of biochemical failure and lower survival rate compared with those with a PSA level of ≤1 ng/mL. Patients without adequate PSA suppression should be considered a higher risk group and considered for dose escalation or the use of novel treatments

  20. Dinucleotide controlled null models for comparative RNA gene prediction

    Directory of Open Access Journals (Sweden)

    Gesell Tanja

    2008-05-01

    Full Text Available Abstract Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require

  1. Dinucleotide controlled null models for comparative RNA gene prediction.

    Science.gov (United States)

    Gesell, Tanja; Washietl, Stefan

    2008-05-27

    Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz

  2. The improvement of PWR(OPR-1000) Local Control Pannel

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Joo-Youl; Kim, Min-Soo; Kim, Kyung-Min; Lee, Jun-Kou [KHNP CRI, Daejeon (Korea, Republic of)

    2016-10-15

    The malfunction of feature in NPP could be occurred by physical aging, electrical false signal and natural disaster. The first recognition of malfunction is almost done by alarm system. Due to the importance of alarm system, design basis of alarm system is described in FSAR 18.1.4.20(alarm system design review). Operators can recognize malfunction of feature and importance of alarm in short distance. The sound of alarm is also changed depending on frequency so it contributes recognition of alarm. This system is not helpful in recognition of alarm for filed operators. In this study, the way that FSAR(priority of alarm and color indication) is also applied on local control is suggested. The alarm sound considering field situation, alarm name, status indication in circuit breaker are suggested to improve overall local control panel. These can contribute to safety operation. This paper is made from improvement items of local control panel in the sight of field operator. The research of local panel is necessary to apply these improvements and the collaboration of related department is also needed. In this study, The alarm sound considering field situation, alarm name, status indication in circuit breaker are suggested to improve overall local control panel based on Hanul Unit 6. If the improvement is applied, the qualitative effect of safe operation will be increased, and fatigue of work stress will be lower.

  3. Neural-Fuzzy Digital Strategy of Continuous-Time Nonlinear Systems Using Adaptive Prediction and Random-Local-Optimization Design

    Directory of Open Access Journals (Sweden)

    Zhi-Ren Tsai

    2013-01-01

    Full Text Available A tracking problem, time-delay, uncertainty and stability analysis of a predictive control system are considered. The predictive control design is based on the input and output of neural plant model (NPM, and a recursive fuzzy predictive tracker has scaling factors which limit the value zone of measured data and cause the tuned parameters to converge to obtain a robust control performance. To improve the further control performance, the proposed random-local-optimization design (RLO for a model/controller uses offline initialization to obtain a near global optimal model/controller. Other issues are the considerations of modeling error, input-delay, sampling distortion, cost, greater flexibility, and highly reliable digital products of the model-based controller for the continuous-time (CT nonlinear system. They are solved by a recommended two-stage control design with the first-stage (offline RLO and second-stage (online adaptive steps. A theorizing method is then put forward to replace the sensitivity calculation, which reduces the calculation of Jacobin matrices of the back-propagation (BP method. Finally, the feedforward input of reference signals helps the digital fuzzy controller improve the control performance, and the technique works to control the CT systems precisely.

  4. Model Predictive Control with Constraints of a Wind Turbine

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Poulsen, Niels Kjølstad

    2007-01-01

    Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure a...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers.......Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...

  5. DeepLoc: prediction of protein subcellular localization using deep learning

    DEFF Research Database (Denmark)

    Almagro Armenteros, Jose Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae

    2017-01-01

    The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from...... knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict...... current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc . Example code is available at https://github.com/JJAlmagro/subcellular_localization . The dataset is available at http...

  6. Power Admission Control with Predictive Thermal Management in Smart Buildings

    DEFF Research Database (Denmark)

    Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan

    2015-01-01

    This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...

  7. Robust controller for synchronous generator with local load via VSC

    Energy Technology Data Exchange (ETDEWEB)

    Cabrera-Vazquez, J. [Universidad de Guadalajara, Centro Universitario de Ciencias Exactas e Ingenierias, Departamento de Electronica, Av. Revolucion No. 1500, Modulo ' ' O' ' , Apdo. Postal 44840, Guadalajara Jalisco (Mexico); Loukianov, Alexander G.; Canedo, Jose M. [Centro de Investigacion y de Estudios Avanzados del IPN, Apdo. Postal 31-438, Plaza La Luna, C. P. 44550, Guadalajara, Jalisco (Mexico); Utkin, Vadim I. [Department of Electrical Engineering, The Ohio-State University, Columbus, OH 43210-1272 (United States)

    2007-05-15

    The objective of this paper is to design a nonlinear observer-based excitation controller for power system comprising a single synchronous generator connected to an infinite bus with local load. The controller proposed is based on the using first singular perturbation systems concepts and then Sliding Mode Control technique combining with Block Control Principle. To reduce ''chattering'' a nonlinear observer with estimation of the mechanical torque and rotor fluxes is designed. This combined approach enables to compensate the inherent nonlinearities of the generator and to reject external disturbances. (author)

  8. Tracking local control of a parabolic trough collector

    International Nuclear Information System (INIS)

    Ajona, J.I.; Alberdi, J.; Gamero, E.; Blanco, J.

    1992-01-01

    In the local control, the sun position related to the trough collector is measured by two photo-resistors. The provided electronic signal is then compared with reference levels in order to get a set of B logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of o P.R.O.M. memory which is programmed with the logical equations of the control system. The memory output lines give the control command of the parabolic trough collector motor. (Author)

  9. Predictive Variable Gain Iterative Learning Control for PMSM

    Directory of Open Access Journals (Sweden)

    Huimin Xu

    2015-01-01

    Full Text Available A predictive variable gain strategy in iterative learning control (ILC is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.

  10. New prediction of chaotic time series based on local Lyapunov exponent

    International Nuclear Information System (INIS)

    Zhang Yong

    2013-01-01

    A new method of predicting chaotic time series is presented based on a local Lyapunov exponent, by quantitatively measuring the exponential rate of separation or attraction of two infinitely close trajectories in state space. After reconstructing state space from one-dimensional chaotic time series, neighboring multiple-state vectors of the predicting point are selected to deduce the prediction formula by using the definition of the local Lyapunov exponent. Numerical simulations are carried out to test its effectiveness and verify its higher precision over two older methods. The effects of the number of referential state vectors and added noise on forecasting accuracy are also studied numerically. (general)

  11. Traffic Predictive Control: Case Study and Evaluation

    Science.gov (United States)

    2017-06-26

    This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...

  12. Model Predictive Controller Combined with LQG Controller and Velocity Feedback to Control the Stewart Platform

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil Sharak; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

    2006-01-01

    The main objective of this paper is to investigate the erformance and applicability of two GPC (generalized predictive control) based control methods on a complete benchmark model of the Stewart platform made in MATLAB V6.5. The first method involves an LQG controller (Linear Quadratic Gaussian...

  13. Local control station for development, testing and maintenance of mirror fusion facility subsystem controls

    International Nuclear Information System (INIS)

    Ables, E.; Kelly, M.F.

    1985-01-01

    A Local Control Station (LCS) was designed and built to provide a simplified ad easily configurable means of controlling any Mirror Fusion Test Facility (MFTF-B) subsystem for the purpose of development, testing and maintenance of the subsystem. All MFTF-B Subsystems incorporate at least one Local Control Computer (LCC) that is connected to and accepts high level commands from one of the Supervisory Control and Diagnostic System (SCDS) computers. The LCS connects directly to the LCC in place of SCDS. The LCS communicates with the subsystem hardware using the same SCDS commands that the local control computer recognizes and as such requires no special configuration of the LCC

  14. Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers

    Science.gov (United States)

    Muñoz, Á. G.; Díaz-Lobatón, J.; Chourio, X.; Stock, M. J.

    2016-05-01

    The Lake Maracaibo Basin in North Western Venezuela has the highest annual lightning rate of any place in the world (~ 200 fl km- 2 yr- 1), whose electrical discharges occasionally impact human and animal lives (e.g., cattle) and frequently affect economic activities like oil and natural gas exploitation. Lightning activity is so common in this region that it has a proper name: Catatumbo Lightning (plural). Although short-term lightning forecasts are now common in different parts of the world, to the best of the authors' knowledge, seasonal prediction of lightning activity is still non-existent. This research discusses the relative role of both large-scale and local climate drivers as modulators of lightning activity in the region, and presents a formal predictability study at seasonal scale. Analysis of the Catatumbo Lightning Regional Mode, defined in terms of the second Empirical Orthogonal Function of monthly Lightning Imaging Sensor (LIS-TRMM) and Optical Transient Detector (OTD) satellite data for North Western South America, permits the identification of potential predictors at seasonal scale via a Canonical Correlation Analysis. Lightning activity in North Western Venezuela responds to well defined sea-surface temperature patterns (e.g., El Niño-Southern Oscillation, Atlantic Meridional Mode) and changes in the low-level meridional wind field that are associated with the Inter-Tropical Convergence Zone migrations, the Caribbean Low Level Jet and tropical cyclone activity, but it is also linked to local drivers like convection triggered by the topographic configuration and the effect of the Maracaibo Basin Nocturnal Low Level Jet. The analysis indicates that at seasonal scale the relative contribution of the large-scale drivers is more important than the local (basin-wide) ones, due to the synoptic control imposed by the former. Furthermore, meridional CAPE transport at 925 mb is identified as the best potential predictor for lightning activity in the Lake

  15. Should Aggressive Surgical Local Control Be Attempted in All Patients with Metastatic or Pelvic Ewing's Sarcoma?

    Science.gov (United States)

    Thorpe, Steven W.; Weiss, Kurt R.; Goodman, Mark A.; Heyl, Alma E.; McGough, Richard L.

    2012-01-01

    In previous reports, patients with Ewing's sarcoma received radiation therapy (XRT) for definitive local control because metastatic disease and pelvic location were thought to preclude aggressive local treatment. We sought to determine if single-site metastatic disease should be treated differently from multicentric-metastatic disease. We also wanted to reinvestigate the impact of XRT, pelvic location, and local recurrence on outcomes. Our results demonstrated a significant difference in overall survival (OS) between patients with either localized disease or a single-metastatic site and patients with multicentric-metastatic disease (P = 0.004). Local control was also found to be an independent predictor of outcomes as demonstrated by a significant difference in OS between those with and without local recurrence (P = 0.001). Axial and pelvic location did not predict a decreased OS. Based on these results, we concluded that pelvic location and the diagnosis of metastatic disease at diagnosis should not preclude aggressive local control, except in cases of multicentric-metastatic disease. PMID:22550427

  16. Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

    Science.gov (United States)

    Hong, S-M; Jung, B-H; Ruan, D

    2011-03-21

    Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

  17. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  18. A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

    Science.gov (United States)

    Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

    2017-10-01

    The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

  19. Model predictive control of smart microgrids

    DEFF Research Database (Denmark)

    Hu, Jiefeng; Zhu, Jianguo; Guerrero, Josep M.

    2014-01-01

    The exploitation of renewable energy and the development of intelligent electricity network have become the main concerns worldwide. This paper aims to integrate renewable energy sources, local loads, and energy storage devices into smart microgrids. It proposes a new microgrid configuration...

  20. Local gate control in carbon nanotube quantum devices

    Science.gov (United States)

    Biercuk, Michael Jordan

    This thesis presents transport measurements of carbon nanotube electronic devices operated in the quantum regime. Nanotubes are contacted by source and drain electrodes, and multiple lithographically-patterned electrostatic gates are aligned to each device. Transport measurements of device conductance or current as a function of local gate voltages reveal that local gates couple primarily to the proximal section of the nanotube, hence providing spatially localized control over carrier density along the nanotube length. Further, using several different techniques we are able to produce local depletion regions along the length of a tube. This phenomenon is explored in detail for different contact metals to the nanotube. We utilize local gating techniques to study multiple quantum dots in carbon nanotubes produced both by naturally occurring defects, and by the controlled application of voltages to depletion gates. We study double quantum dots in detail, where transport measurements reveal honeycomb charge stability diagrams. We extract values of energy-level spacings, capacitances, and interaction energies for this system, and demonstrate independent control over all relevant tunneling rates. We report rf-reflectometry measurements of gate-defined carbon nanotube quantum dots with integrated charge sensors. Aluminum rf-SETs are electrostatically coupled to carbon nanotube devices and detect single electron charging phenomena in the Coulomb blockade regime. Simultaneous correlated measurements of single electron charging are made using reflected rf power from the nanotube itself and from the rf-SET on microsecond time scales. We map charge stability diagrams for the nanotube quantum dot via charge sensing, observing Coulomb charging diamonds beyond the first order. Conductance measurements of carbon nanotubes containing gated local depletion regions exhibit plateaus as a function of gate voltage, spaced by approximately 1e2/h, the quantum of conductance for a single

  1. Outdoor flocking of quadcopter drones with decentralized model predictive control.

    Science.gov (United States)

    Yuan, Quan; Zhan, Jingyuan; Li, Xiang

    2017-11-01

    In this paper, we present a multi-drone system featured with a decentralized model predictive control (DMPC) flocking algorithm. The drones gather localized information from neighbors and update their velocities using the DMPC flocking algorithm. In the multi-drone system, data packages are transmitted through XBee ® wireless modules in broadcast mode, yielding such an anonymous and decentralized system where all the calculations and controls are completed on an onboard minicomputer of each drone. Each drone is a double-layered agent system with the coordination layer running multi-drone flocking algorithms and the flight control layer navigating the drone, and the final formation of the flock relies on both the communication range and the desired inter-drone distance. We give both numerical simulations and field tests with a flock of five drones, showing that the DMPC flocking algorithm performs well on the presented multi-drone system in both the convergence rate and the ability of tracking a desired path. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Improved local control with neoadjuvant chemotherapy for locally advanced rectal carcinoma: Long-term analysis

    International Nuclear Information System (INIS)

    Nakfoor, Bruce M.; Willett, Christopher G.; Kaufman, S. Donald; Shellito, Paul C.; Daly, William J.

    1996-01-01

    Objective: Since 1979, our institution has treated locally advanced rectal cancer with preoperative irradiation followed by resection with or without intraoperative radiation therapy (IORT). In 1986, our preoperative treatment policy was changed to include bolus 5-FU chemotherapy concurrent with irradiation in hopes of improving resectability, downstaging and/or local control rates. We report the long-term results with the addition of 5-FU chemotherapy to preoperative irradiation. Materials and Methods: From 1979 - 1994, 200 patients with locally advanced rectal carcinoma (primary or recurrent) received preoperative irradiation, resection and IORT if indicated. Bolus 5-FU (500mg/m 2 /day) chemotherapy was administered for three days during weeks one and five of irradiation. The change in treatment policy was limited to the addition of 5-FU chemotherapy: the radiation techniques (four-field), doses (50.4 Gy), and indications for intraoperative radiation (microscopic residual, gross residual, tumor adherence) remained constant. The median follow-up for the entire group of patients was 33 months (.95 months - 199 months), and the minimum follow-up was 1.5 years. Tabular results are 5-year actuarial calculations. Results: One hundred and five patients received preoperative 5-FU chemotherapy and irradiation whereas 95 patients underwent preoperative irradiation alone. Sixty-five percent of the patients were able to undergo complete resections, and 53% had transmural disease upon pathologic examination. The addition of chemotherapy did not affect the rates of resectability or tumor downstaging. However, the 10-year local control rate was significantly improved for those patients who received preoperative chemotherapy: 77% vs. 44% (p<0.01) (see figure). When stratified by extent of resection and stage, those patients who underwent complete resections or had transmural disease had significantly improved local control rates when compared to the non-chemotherapy group: No

  3. Climate control loads prediction of electric vehicles

    International Nuclear Information System (INIS)

    Zhang, Ziqi; Li, Wanyong; Zhang, Chengquan; Chen, Jiangping

    2017-01-01

    Highlights: • A model of vehicle climate control loads is proposed based on experiments. • Main climate control loads of the modeled vehicle are quantitatively analyzed. • Range reductions of the modeled vehicle under different conditions are simulated. - Abstract: A new model of electric vehicle climate control loads is provided in this paper. The mathematical formulations of the major climate control loads are developed, and the coefficients of the formulations are experimentally determined. Then, the detailed climate control loads are analyzed, and the New European Driving Cycle (NEDC) range reductions due to these loads are calculated under different conditions. It is found that in an electric vehicle, the total climate control loads vary with the vehicle speed, HVAC mode and blower level. The ventilation load is the largest climate control load, followed by the solar radiation load. These two add up to more than 80% of total climate control load in summer. The ventilation load accounts for 70.7–83.9% of total heating load under the winter condition. The climate control loads will cause a 17.2–37.1% reduction of NEDC range in summer, and a 17.1–54.1% reduction in winter, compared to the AC off condition. The heat pump system has an advantage in range extension. A heat pump system with an average heating COP of 1.7 will extend the range by 7.6–21.1% based on the simulation conditions.

  4. Prediction of protein subcellular localization using support vector machine with the choice of proper kernel

    Directory of Open Access Journals (Sweden)

    Al Mehedi Hasan

    2017-07-01

    Full Text Available The prediction of subcellular locations of proteins can provide useful hints for revealing their functions as well as for understanding the mechanisms of some diseases and, finally, for developing novel drugs. As the number of newly discovered proteins has been growing exponentially, laboratory-based experiments to determine the location of an uncharacterized protein in a living cell have become both expensive and time-consuming. Consequently, to tackle these challenges, computational methods are being developed as an alternative to help biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging problem, particularly when query proteins may have multi-label characteristics, i.e. their simultaneous existence in more than one subcellular location, or if they move between two or more different subcellular locations as well. At this point, to get rid of this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM has been employed to provide potential solutions for problems connected with the prediction of protein subcellular localization. However, the practicability of SVM is affected by difficulties in selecting its appropriate kernel as well as in selecting the parameters of that selected kernel. The literature survey has shown that most researchers apply the radial basis function (RBF kernel to build a SVM based subcellular localization prediction system. Surprisingly, there are still many other kernel functions which have not yet been applied in the prediction of protein subcellular localization. However, the nature of this classification problem requires the application of different kernels for SVM to ensure an optimal result. From this viewpoint, this paper presents the work to apply different kernels for SVM in protein

  5. Prediction based chaos control via a new neural network

    International Nuclear Information System (INIS)

    Shen Liqun; Wang Mao; Liu Wanyu; Sun Guanghui

    2008-01-01

    In this Letter, a new chaos control scheme based on chaos prediction is proposed. To perform chaos prediction, a new neural network architecture for complex nonlinear approximation is proposed. And the difficulty in building and training the neural network is also reduced. Simulation results of Logistic map and Lorenz system show the effectiveness of the proposed chaos control scheme and the proposed neural network

  6. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  7. Ciudadania, el poder local e controle do Estado

    Directory of Open Access Journals (Sweden)

    Angela Moulin Simões Penalva Santos

    2004-01-01

    Full Text Available Brazilian society is experiencing a population expansion within the context of decentralisation of public policies, from the central government to local institutions. Following this line of thought, in this article we analyse the public expenses in the Brazilian Federation in the period 1996-1998 in order to identify the institutions that have assumed the financial right of the citizens, as well as to estimate if there has been a transfer of responsibilities among federal institutions. The success of this process is related to the integrated performance of the external control from the public administration. In that sense, we also study the control exercised by Parliaments, Administrative Courts, Public Prosecution Offices and the Judicial Power beyond social control, taking into consideration their improvement and highlighting the control of the Public Prosecution Office as well as the control exercised by the popular councils.

  8. Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

    Directory of Open Access Journals (Sweden)

    Lee Sael

    2010-12-01

    Full Text Available Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

  9. Binding ligand prediction for proteins using partial matching of local surface patches.

    Science.gov (United States)

    Sael, Lee; Kihara, Daisuke

    2010-01-01

    Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

  10. Reducing prediction uncertainty of weather controlled systems

    NARCIS (Netherlands)

    Doeswijk, T.G.

    2007-01-01

    In closed agricultural systems the weather acts both as a disturbance and as a resource. By using weather forecasts in control strategies the effects of disturbances can be minimized whereas the resources can be utilized. In this situation weather forecast uncertainty and model based control are

  11. Model predictive control of a crude oil distillation column

    Directory of Open Access Journals (Sweden)

    Morten Hovd

    1999-04-01

    Full Text Available The project of designing and implementing model based predictive control on the vacuum distillation column at the Nynäshamn Refinery of Nynäs AB is described in this paper. The paper describes in detail the modeling for the model based control, covers the controller implementation, and documents the benefits gained from the model based controller.

  12. PRMT1-mediated arginine methylation controls ATXN2L localization

    Energy Technology Data Exchange (ETDEWEB)

    Kaehler, Christian; Guenther, Anika; Uhlich, Anja; Krobitsch, Sylvia, E-mail: krobitsc@molgen.mpg.de

    2015-05-15

    Arginine methylation is a posttranslational modification that is of importance in diverse cellular processes. Recent proteomic mass spectrometry studies reported arginine methylation of ataxin-2-like (ATXN2L), the paralog of ataxin-2, a protein that is implicated in the neurodegenerative disorder spinocerebellar ataxia type 2. Here, we investigated the methylation state of ATXN2L and its significance for ATXN2L localization. We first confirmed that ATXN2L is asymmetrically dimethylated in vivo, and observed that the nuclear localization of ATXN2L is altered under methylation inhibition. We further discovered that ATXN2L associates with the protein arginine-N-methyltransferase 1 (PRMT1). Finally, we showed that neither mutation of the arginine–glycine-rich motifs of ATXN2L nor methylation inhibition alters ATXN2L localization to stress granules, suggesting that methylation of ATXN2L is probably not mandatory. - Highlights: • ATXN2L is asymmetrically dimethylated in vivo. • ATXN2L interacts with PRMT1 under normal and stress conditions. • PRMT1-mediated dimethylation of ATXN2L controls its nuclear localization. • ATXN2L localization to stress granules appears independent of its methylation state.

  13. Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian

    Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...

  14. Tuberculosis control: decentralization, local planning and management specificities.

    Science.gov (United States)

    Trigueiro, Janaína Von Söhsten; Nogueira, Jordana de Almeida; de Sá, Lenilde Duarte; Palha, Pedro Fredemir; Villa, Tereza Cristina Scatena; Trigueiro, Débora Raquel Soares Guedes

    2011-01-01

    The goal was to analyze, according to the perception of health managers, the practices that guide tuberculosis control actions in cities in the metropolitan region of João Pessoa - PB, Brazil. This qualitative study involved eight professionals in management functions. Testimonies were collected through semi-structured interviews between May and June 2009 and organized through content analysis. Despite the acknowledged benefits of tuberculosis control action decentralization, local planning indicates the predominance of a bureaucratic model that is restricted to negotiation and supplies. Local programming is centered on the coordinator, which shows a command line and vertical management that lead to the fragmentation of the work process. Management action should follow an innovative and transformative route that surpasses bureaucratic barriers and faces the biggest challenge it is proposed: to balance professional interrelations with a view to improving health work performance.

  15. A study of fatigue life prediction for automotive spot weldment using local strain approach

    International Nuclear Information System (INIS)

    Lee, Song In; Yu, Hyo Sun; Na, Sung Hun; Na, Eui Gyun

    2000-01-01

    The fatigue crack initiation life is studied on automotive spot weldment made from cold rolled carbon steel(SPC) sheet by using DCPDM and local strain approach. It can be found that the fatigue crack initiation behavior in spot weldment can be definitely detected by DCPDM system. The local stresses and strains are estimated by elastic-plastic FEM analysis and the alternative approximate method based on Neuber's rule were applied to predict the fatigue life of spot weldment. A satisfactory correlation between the predicted life and experimental life can be found in spot weldment within a factor of 4

  16. Determinates of tumor response to radiation: Tumor cells, tumor stroma and permanent local control

    International Nuclear Information System (INIS)

    Li, Wende; Huang, Peigen; Chen, David J.; Gerweck, Leo E.

    2014-01-01

    Background and purpose: The causes of tumor response variation to radiation remain obscure, thus hampering the development of predictive assays and strategies to decrease resistance. The present study evaluates the impact of host tumor stromal elements and the in vivo environment on tumor cell kill, and relationship between tumor cell radiosensitivity and the tumor control dose. Material and methods: Five endpoints were evaluated and compared in a radiosensitive DNA double-strand break repair-defective (DNA-PKcs −/− ) tumor line, and its DNA-PKcs repair competent transfected counterpart. In vitro colony formation assays were performed on in vitro cultured cells, on cells obtained directly from tumors, and on cells irradiated in situ. Permanent local control was assessed by the TCD 50 assay. Vascular effects were evaluated by functional vascular density assays. Results: The fraction of repair competent and repair deficient tumor cells surviving radiation did not substantially differ whether irradiated in vitro, i.e., in the absence of host stromal elements and factors, from the fraction of cells killed following in vivo irradiation. Additionally, the altered tumor cell sensitivity resulted in a proportional change in the dose required to achieve permanent local control. The estimated number of tumor cells per tumor, their cloning efficiency and radiosensitivity, all assessed by in vitro assays, were used to predict successfully, the measured tumor control doses. Conclusion: The number of clonogens per tumor and their radiosensitivity govern the permanent local control dose

  17. Comparison Analysis of Model Predictive Controller with Classical PID Controller For pH Control Process

    Directory of Open Access Journals (Sweden)

    V. Balaji

    2016-12-01

    Full Text Available pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing   technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT model controlled by Proportional Integral Derivative (PID and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.

  18. Model Predictive Vibration Control Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures

    CERN Document Server

    Takács, Gergely

    2012-01-01

    Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: ·         the implementation of ...

  19. Predictive Control Based upon State Space Models

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen

    1989-04-01

    Full Text Available Repetitive online computation of the control vector by solving the optimal control problem of a non-linear multivariable process with arbitrary performance indices is investigated. Two different methods are considered in the search for an optimal, parameterized control vector: Pontryagin's Maximum Principle and optimization by using the performance index and its gradient directly. Unfortunately, solving this optimization problem has turned out to be a rather time-consuming task which has resulted in a time delay that cannot be accepted when the actual process is exposed to rapidly-varying disturbances. However, an instantaneous feedback strategy operating in parallel with the original control aogorithm was found to be able to cope with this problem.

  20. Stability Constraints for Robust Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Amanda G. S. Ottoni

    2015-01-01

    Full Text Available This paper proposes an approach for the robust stabilization of systems controlled by MPC strategies. Uncertain SISO linear systems with box-bounded parametric uncertainties are considered. The proposed approach delivers some constraints on the control inputs which impose sufficient conditions for the convergence of the system output. These stability constraints can be included in the set of constraints dealt with by existing MPC design strategies, in this way leading to the “robustification” of the MPC.

  1. ngLOC: software and web server for predicting protein subcellular localization in prokaryotes and eukaryotes

    Directory of Open Access Journals (Sweden)

    King Brian R

    2012-07-01

    Full Text Available Abstract Background Understanding protein subcellular localization is a necessary component toward understanding the overall function of a protein. Numerous computational methods have been published over the past decade, with varying degrees of success. Despite the large number of published methods in this area, only a small fraction of them are available for researchers to use in their own studies. Of those that are available, many are limited by predicting only a small number of organelles in the cell. Additionally, the majority of methods predict only a single location for a sequence, even though it is known that a large fraction of the proteins in eukaryotic species shuttle between locations to carry out their function. Findings We present a software package and a web server for predicting the subcellular localization of protein sequences based on the ngLOC method. ngLOC is an n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The overall prediction accuracy varies from 89.8% to 91.4% across species. This program can predict 11 distinct locations each in plant and animal species. ngLOC also predicts 4 and 5 distinct locations on gram-positive and gram-negative bacterial datasets, respectively. Conclusions ngLOC is a generic method that can be trained by data from a variety of species or classes for predicting protein subcellular localization. The standalone software is freely available for academic use under GNU GPL, and the ngLOC web server is also accessible at http://ngloc.unmc.edu.

  2. Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

    International Nuclear Information System (INIS)

    Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

    2015-01-01

    Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug–target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

  3. Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

    Science.gov (United States)

    Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

    2015-11-01

    Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

  4. MU-LOC: A Machine-Learning Method for Predicting Mitochondrially Localized Proteins in Plants

    Directory of Open Access Journals (Sweden)

    Ning Zhang

    2018-05-01

    Full Text Available Targeting and translocation of proteins to the appropriate subcellular compartments are crucial for cell organization and function. Newly synthesized proteins are transported to mitochondria with the assistance of complex targeting sequences containing either an N-terminal pre-sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale prediction of plant mitochondrial proteins. We collected a comprehensive dataset of plant subcellular localization, extracted features including amino acid composition, protein position weight matrix, and gene co-expression information, and trained predictors using deep neural network and support vector machine. Benchmarked on two independent datasets, MU-LOC achieved substantial improvements over six state-of-the-art tools for plant mitochondrial targeting prediction. In addition, MU-LOC has the advantage of predicting plant mitochondrial proteins either possessing or lacking N-terminal pre-sequences. We applied MU-LOC to predict candidate mitochondrial proteins for the whole proteome of Arabidopsis and potato. MU-LOC is publicly available at http://mu-loc.org.

  5. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    Science.gov (United States)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  6. Model predictive control for spacecraft rendezvous in elliptical orbit

    Science.gov (United States)

    Li, Peng; Zhu, Zheng H.

    2018-05-01

    This paper studies the control of spacecraft rendezvous with attitude stable or spinning targets in an elliptical orbit. The linearized Tschauner-Hempel equation is used to describe the motion of spacecraft and the problem is formulated by model predictive control. The control objective is to maximize control accuracy and smoothness simultaneously to avoid unexpected change or overshoot of trajectory for safe rendezvous. It is achieved by minimizing the weighted summations of control errors and increments. The effects of two sets of horizons (control and predictive horizons) in the model predictive control are examined in terms of fuel consumption, rendezvous time and computational effort. The numerical results show the proposed control strategy is effective.

  7. Multiple descriptions for packetized predictive control

    DEFF Research Database (Denmark)

    Østergaard, Jan; Quevedo, Daniel

    2016-01-01

    be reliably reconstructed at the plant side. For the particular case of LTI plant models and i.i.d. channels, we show that the overall system forms a Markov jump linear system. We provide conditions for mean square stability and derive upper bounds on the operational bit rate of the quantizer to guarantee......In this paper, we propose to use multiple descriptions (MDs) to achieve a high degree of robustness towards random packet delays and erasures in networked control systems. In particular, we consider the scenario, where a data-rate limited channel is located between the controller and the plant...

  8. Meteorological Controls on Local and Regional Volcanic Ash Dispersal.

    Science.gov (United States)

    Poulidis, Alexandros P; Phillips, Jeremy C; Renfrew, Ian A; Barclay, Jenni; Hogg, Andrew; Jenkins, Susanna F; Robertson, Richard; Pyle, David M

    2018-05-02

    Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume.

  9. Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

    Science.gov (United States)

    Dussaillant, Francisca; Apablaza, Mauricio

    2017-08-01

    After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

  10. A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

    International Nuclear Information System (INIS)

    Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

    2013-01-01

    Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

  11. Fault Predictive Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Wickerhauser, Mladen Victor

    2006-01-01

    Optical disc players such as CD-players have problems playing certain discs with surface faults like scratches and fingerprints. The problem is to be found in the servo controller which positions the optical pick-up, such that the laser beam is focused on the information track. A scheme handling...

  12. Extension of local front reconstruction method with controlled coalescence model

    Science.gov (United States)

    Rajkotwala, A. H.; Mirsandi, H.; Peters, E. A. J. F.; Baltussen, M. W.; van der Geld, C. W. M.; Kuerten, J. G. M.; Kuipers, J. A. M.

    2018-02-01

    The physics of droplet collisions involves a wide range of length scales. This poses a challenge to accurately simulate such flows with standard fixed grid methods due to their inability to resolve all relevant scales with an affordable number of computational grid cells. A solution is to couple a fixed grid method with subgrid models that account for microscale effects. In this paper, we improved and extended the Local Front Reconstruction Method (LFRM) with a film drainage model of Zang and Law [Phys. Fluids 23, 042102 (2011)]. The new framework is first validated by (near) head-on collision of two equal tetradecane droplets using experimental film drainage times. When the experimental film drainage times are used, the LFRM method is better in predicting the droplet collisions, especially at high velocity in comparison with other fixed grid methods (i.e., the front tracking method and the coupled level set and volume of fluid method). When the film drainage model is invoked, the method shows a good qualitative match with experiments, but a quantitative correspondence of the predicted film drainage time with the experimental drainage time is not obtained indicating that further development of film drainage model is required. However, it can be safely concluded that the LFRM coupled with film drainage models is much better in predicting the collision dynamics than the traditional methods.

  13. French local agencies of energy control; Agences locales francaise de maitrise de l'energie

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-07-01

    In the framework of the SAVE program, the European Commission brings financial assistance to the creation of local or regional agencies of energy control in municipalities and regions. The main criteria are the impacts on the energy demand, the reinforcement of the economic and social cohesion, the environmental quality and the contribution to the economic development and the employment creation. In this document, realized by Energie-Cites, the Ademe objective is to present a state of the art of french local agencies. Ten agencies are presented as case study. Each case deals with the following topics: the main context of the action which details the energy and the environmental policy of the municipality, the creation and the description of the agency, the implemented actions and the perspectives. (A.L.B.)

  14. French local agencies of energy control; Agences locales francaise de maitrise de l'energie

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-07-01

    In the framework of the SAVE program, the European Commission brings financial assistance to the creation of local or regional agencies of energy control in municipalities and regions. The main criteria are the impacts on the energy demand, the reinforcement of the economic and social cohesion, the environmental quality and the contribution to the economic development and the employment creation. In this document, realized by Energie-Cites, the Ademe objective is to present a state of the art of french local agencies. Ten agencies are presented as case study. Each case deals with the following topics: the main context of the action which details the energy and the environmental policy of the municipality, the creation and the description of the agency, the implemented actions and the perspectives. (A.L.B.)

  15. Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2016-01-01

    Full Text Available The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs, are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.

  16. Robot trajectory tracking with self-tuning predicted control

    Science.gov (United States)

    Cui, Xianzhong; Shin, Kang G.

    1988-01-01

    A controller that combines self-tuning prediction and control is proposed for robot trajectory tracking. The controller has two feedback loops: one is used to minimize the prediction error, and the other is designed to make the system output track the set point input. Because the velocity and position along the desired trajectory are given and the future output of the system is predictable, a feedforward loop can be designed for robot trajectory tracking with self-tuning predicted control (STPC). Parameters are estimated online to account for the model uncertainty and the time-varying property of the system. The authors describe the principle of STPC, analyze the system performance, and discuss the simplification of the robot dynamic equations. To demonstrate its utility and power, the controller is simulated for a Stanford arm.

  17. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  18. Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method

    DEFF Research Database (Denmark)

    Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua

    2014-01-01

    the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...

  19. Protein Sub-Nuclear Localization Prediction Using SVM and Pfam Domain Information

    Science.gov (United States)

    Kumar, Ravindra; Jain, Sohni; Kumari, Bandana; Kumar, Manish

    2014-01-01

    The nucleus is the largest and the highly organized organelle of eukaryotic cells. Within nucleus exist a number of pseudo-compartments, which are not separated by any membrane, yet each of them contains only a specific set of proteins. Understanding protein sub-nuclear localization can hence be an important step towards understanding biological functions of the nucleus. Here we have described a method, SubNucPred developed by us for predicting the sub-nuclear localization of proteins. This method predicts protein localization for 10 different sub-nuclear locations sequentially by combining presence or absence of unique Pfam domain and amino acid composition based SVM model. The prediction accuracy during leave-one-out cross-validation for centromeric proteins was 85.05%, for chromosomal proteins 76.85%, for nuclear speckle proteins 81.27%, for nucleolar proteins 81.79%, for nuclear envelope proteins 79.37%, for nuclear matrix proteins 77.78%, for nucleoplasm proteins 76.98%, for nuclear pore complex proteins 88.89%, for PML body proteins 75.40% and for telomeric proteins it was 83.33%. Comparison with other reported methods showed that SubNucPred performs better than existing methods. A web-server for predicting protein sub-nuclear localization named SubNucPred has been established at http://14.139.227.92/mkumar/subnucpred/. Standalone version of SubNucPred can also be downloaded from the web-server. PMID:24897370

  20. Local predation pressure predicts the strength of mobbing responses in tropical birds

    Directory of Open Access Journals (Sweden)

    Luis SANDOVAL, David R. WILSON

    2012-10-01

    Full Text Available Many birds join cooperative mobbing aggregations and collectively harass predators. Individuals participating in these ephemeral associations benefit by deterring the predator, but also incur energetic costs and increased risk of predation. Explaining the evolution of mobbing is challenging because individuals could prevail by selfishly seeking safety while allowing others to mob. An important step in understanding the evolution of mobbing is to identify factors affecting its expression. The ecological constraints model suggests that animals are more likely to cooperate under adverse environmental conditions, such as when local predation pressure is high. We tested this prediction by comparing the mobbing responses of several species of birds to the local abundance of their primary predator, the ferruginous pygmy-owl Glaucidium brasilianum. We used acoustic playback to elicit mobbing responses in environments where owls were common, uncommon, or rare. Stimuli were either the song of a ferruginous pygmy-owl or the mobbing calls of three of the owl’s common prey species. During each playback, we characterized mobbing responses by noting the number of species and individuals that approached the loudspeaker, as well as the closest approach by any bird. Mobbing responses to both stimuli were strong in locations where Ferruginous Pygmy-owls were common, intermediate where owls were uncommon, and weak where they were rare. This pattern persisted even after controlling for differences in species richness and composition among the three environments. Results support the ecological constraints model and provide strong evidence that intense predation pressure increases the expression of cooperative mobbing in tropical birds [Current Zoology 58 (5: 781-790, 2012].

  1. Model Predictive Control Algorithms for Pen and Pump Insulin Administration

    DEFF Research Database (Denmark)

    Boiroux, Dimitri

    at mealtime, and the case where the insulin sensitivity increases during the night. This thesis consists of a summary report, glucose and insulin proles of the clinical studies and research papers submitted, peer-reviewed and/or published in the period September 2009 - September 2012....... of current closed-loop controllers. In this thesis, we present different control strategies based on Model Predictive Control (MPC) for an artificial pancreas. We use Nonlinear Model Predictive Control (NMPC) in order to determine the optimal insulin and blood glucose profiles. The optimal control problem...

  2. Adaptive chaos control and synchronization in only locally Lipschitz systems

    International Nuclear Information System (INIS)

    Lin Wei

    2008-01-01

    In the existing results on chaos control and synchronization based on the adaptive controlling technique (ACT), a uniform Lipschitz condition on a given dynamical system is always assumed in advance. However, without this uniform Lipschitz condition, the ACT might be failed in both theoretical analysis and in numerical experiment. This Letter shows how to utilize the ACT to get a rigorous control for the system which is not uniformly Lipschitz but only locally Lipschitz, and even for the system which has unbounded trajectories. In fact, the ACT is proved to possess some limitation, which is actually induced by the nonlinear degree of the original system. Consequently, a piecewise ACT is proposed so as to improve the performance of the existing techniques

  3. Software for the Local Control and Instrumentation System for MFTF

    International Nuclear Information System (INIS)

    Labiak, W.G.

    1979-01-01

    There are nine different systems requiring over fifty computers in the Local Control and Instrumentation System for the Mirror Fusion Test Facility. Each computer system consists of an LSI-11/2 processor with 32,000 words of memory, a serial driver that implements the CAMAC serial highway protocol. With this large number of systems it is important that as much software as possible be common to all systems. A serial communications system has been developed for data transfers between the LSI-11/2's and the supervisory computers. This system is based on the RS 232 C interface with modem control lines. Six modem control lines are used for hardware handshaking, which allows totally independent full duplex communications to occur. Odd parity on each byte and a 16-bit checksum are used to detect errors in transmission

  4. Control of group of mobile autonomous agents via local strategies

    Institute of Scientific and Technical Information of China (English)

    Lixin GAO; Daizhan CHENG; Yiguang HONG

    2008-01-01

    This paper considers the formation control problem of multi-agent systems in a distributed fashion.Two cases of the information propagating topologies among multiple agents,characterized by graphics model,are considered.One is fixed topology.The other is switching topology which represents the limited and less reliable information exchange.The local formation control strategies established in this paper are based on a simple modification of the existing consensus control strategies.Moreover,some existing convergence conditions ale shown to be a special case of our model even in the continuous-time consensus case.Therefore.the results of this paper extend the existing results about the consensus problem.

  5. Distributed Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus Fogtmann; Vandenberghe, Lieven; Poulsen, Niels Kjølstad

    2016-01-01

    Integration of a large number of flexible consumers in a smart grid requires a scalable power balancing strategy. We formulate the control problem as an optimization problem to be solved repeatedly by the aggregator in a model predictive control framework. To solve the large-scale control problem...

  6. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

  7. Model predictive control for Z-source power converter

    DEFF Research Database (Denmark)

    Mo, W.; Loh, P.C.; Blaabjerg, Frede

    2011-01-01

    This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...

  8. Fourier transform wavefront control with adaptive prediction of the atmosphere.

    Science.gov (United States)

    Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

    2007-09-01

    Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

  9. Robust predictive control strategy applied for propofol dosing using BIS as a controlled variable during anesthesia

    NARCIS (Netherlands)

    Ionescu, Clara A.; De Keyser, Robin; Torrico, Bismark Claure; De Smet, Tom; Struys, Michel M. R. F.; Normey-Rico, Julio E.

    This paper presents the application of predictive control to drug dosing during anesthesia in patients undergoing surgery. The performance of a generic predictive control strategy in drug dosing control, with a previously reported anesthesia-specific control algorithm, has been evaluated. The

  10. Localization of the brainstem GABAergic neurons controlling paradoxical (REM sleep.

    Directory of Open Access Journals (Sweden)

    Emilie Sapin

    Full Text Available Paradoxical sleep (PS is a state characterized by cortical activation, rapid eye movements and muscle atonia. Fifty years after its discovery, the neuronal network responsible for the genesis of PS has been only partially identified. We recently proposed that GABAergic neurons would have a pivotal role in that network. To localize these GABAergic neurons, we combined immunohistochemical detection of Fos with non-radioactive in situ hybridization of GAD67 mRNA (GABA synthesis enzyme in control rats, rats deprived of PS for 72 h and rats allowed to recover after such deprivation. Here we show that GABAergic neurons gating PS (PS-off neurons are principally located in the ventrolateral periaqueductal gray (vlPAG and the dorsal part of the deep mesencephalic reticular nucleus immediately ventral to it (dDpMe. Furthermore, iontophoretic application of muscimol for 20 min in this area in head-restrained rats induced a strong and significant increase in PS quantities compared to saline. In addition, we found a large number of GABAergic PS-on neurons in the vlPAG/dDPMe region and the medullary reticular nuclei known to generate muscle atonia during PS. Finally, we showed that PS-on neurons triggering PS localized in the SLD are not GABAergic. Altogether, our results indicate that multiple populations of PS-on GABAergic neurons are distributed in the brainstem while only one population of PS-off GABAergic neurons localized in the vlPAG/dDpMe region exist. From these results, we propose a revised model for PS control in which GABAergic PS-on and PS-off neurons localized in the vlPAG/dDPMe region play leading roles.

  11. Political control and perceptions of corruption in Icelandic local government

    Directory of Open Access Journals (Sweden)

    Gunnar Helgi Kristinsson

    2015-06-01

    Full Text Available Political control is an important value of democratic governance and without it democratic accountability can hardly mean much. This is why a number of authors have seen politicization of public service appointments and greater control by the centre as a potential counterweight against trends in recent decades towards more networked and less hierarchical organizational forms of directing public policy. It may help to reassert democratic control. The option of strengthening political control, however, has not been much studied with regard to its likely effects on corruption. Power has the potential to corrupt unless adequately controlled and strengthening political power in a networked environment may create a structure of temptation which conventional deterrents to corruption are unable to curb. The impact of strong political leadership on corruption is here studied in the context of Icelandic local government, making use of institutional variations in the office of Mayor, which provide a unique opportunity for testing the effects of strong political control on corruption. The analysis indicates that municipalities with strong political mayors are likely to be associated with perceptions of corruption even when other factors, such as the structure of temptation and deterrents, are accounted for.

  12. Enhanced Control for Local Helicity Injection on the Pegasus ST

    Science.gov (United States)

    Pierren, C.; Bongard, M. W.; Fonck, R. J.; Lewicki, B. T.; Perry, J. M.

    2017-10-01

    Local helicity injection (LHI) experiments on Pegasus rely upon programmable control of a 250 MVA modular power supply system that drives the electromagnets and helicity injection systems. Precise control of the central solenoid is critical to experimental campaigns that test the LHI Taylor relaxation limit and the coupling efficiency of LHI-produced plasmas to Ohmic current drive. Enhancement and expansion of the present control system is underway using field programmable gate array (FPGA) technology for digital logic and control, coupled to new 10 MHz optical-to-digital transceivers for semiconductor level device communication. The system accepts optical command signals from existing analog feedback controllers, transmits them to multiple devices in parallel H-bridges, and aggregates their status signals for fault detection. Present device-level multiplexing/de-multiplexing and protection logic is extended to include bridge-level protections with the FPGA. An input command filter protects against erroneous and/or spurious noise generated commands that could otherwise cause device failures. Fault registration and response times with the FPGA system are 25 ns. Initial system testing indicates an increased immunity to power supply induced noise, enabling plasma operations at higher working capacitor bank voltage. This can increase the applied helicity injection drive voltage, enable longer pulse lengths and improve Ohmic loop voltage control. Work supported by US DOE Grant DE-FG02-96ER54375.

  13. Selection of References in Wind Turbine Model Predictive Control Design

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Hovgaard, Tobias

    2015-01-01

    a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

  14. Moment based model predictive control for systems with additive uncertainty

    NARCIS (Netherlands)

    Saltik, M.B.; Ozkan, L.; Weiland, S.; Ludlage, J.H.A.

    2017-01-01

    In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We

  15. Highly tunable local gate controlled complementary graphene device performing as inverter and voltage controlled resistor.

    Science.gov (United States)

    Kim, Wonjae; Riikonen, Juha; Li, Changfeng; Chen, Ya; Lipsanen, Harri

    2013-10-04

    Using single-layer CVD graphene, a complementary field effect transistor (FET) device is fabricated on the top of separated back-gates. The local back-gate control of the transistors, which operate with low bias at room temperature, enables highly tunable device characteristics due to separate control over electrostatic doping of the channels. Local back-gating allows control of the doping level independently of the supply voltage, which enables device operation with very low VDD. Controllable characteristics also allow the compensation of variation in the unintentional doping typically observed in CVD graphene. Moreover, both p-n and n-p configurations of FETs can be achieved by electrostatic doping using the local back-gate. Therefore, the device operation can also be switched from inverter to voltage controlled resistor, opening new possibilities in using graphene in logic circuitry.

  16. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    Science.gov (United States)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  17. Typing Local Control and State Using Flow Analysis

    Science.gov (United States)

    Guha, Arjun; Saftoiu, Claudiu; Krishnamurthi, Shriram

    Programs written in scripting languages employ idioms that confound conventional type systems. In this paper, we highlight one important set of related idioms: the use of local control and state to reason informally about types. To address these idioms, we formalize run-time tags and their relationship to types, and use these to present a novel strategy to integrate typing with flow analysis in a modular way. We demonstrate that in our separation of typing and flow analysis, each component remains conventional, their composition is simple, but the result can handle these idioms better than either one alone.

  18. Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

    Science.gov (United States)

    Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

    2017-07-01

    Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

  19. Model Predictive Control of a Wave Energy Converter

    DEFF Research Database (Denmark)

    Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard

    2015-01-01

    In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model...... connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPC...

  20. A multicontroller structure for teaching and designing predictive control strategies

    International Nuclear Information System (INIS)

    Hodouin, D.; Desbiens, A.

    1999-01-01

    The paper deals with the unification of the existing linear control algorithms in order to facilitate their transfer to the engineering students and to industry's engineers. The resulting control algorithm is the Global Predictive Control (GlobPC), which is now taught at the graduate and continuing education levels. GlobPC is based on an internal model framework where three independent control criteria are minimized: one for tracking, one for regulation and one for feedforward. This structure allows to obtain desired tracking, regulation and feedforward behaviors in an optimal way while keeping them perfectly separated. It also cleanly separates the deterministic and stochastic predictions of the process model output. (author)

  1. Robust Output Model Predictive Control of an Unstable Rijke Tube

    Directory of Open Access Journals (Sweden)

    Fabian Jarmolowitz

    2012-01-01

    Full Text Available This work investigates the active control of an unstable Rijke tube using robust output model predictive control (RMPC. As internal model a polytopic linear system with constraints is assumed to account for uncertainties. For guaranteed stability, a linear state feedback controller is designed using linear matrix inequalities and used within a feedback formulation of the model predictive controller. For state estimation a robust gain-scheduled observer is developed. It is shown that the proposed RMPC ensures robust stability under constraints over the considered operating range.

  2. Local system for control by console-mobile crane for russian depository of fissionable materials

    International Nuclear Information System (INIS)

    Troshchenko, V.G.; Kapustin, V.N.; Zinina, N.V.; Derbyshev, S.A.

    2005-01-01

    Description of crane of console-mobile type used for transportation of fissionable materials in depository with local control system is represented. Local control system realizes program control in real time [ru

  3. Scanning laser Doppler imaging may predict disease progression of localized scleroderma in children and young adults.

    Science.gov (United States)

    Shaw, L J; Shipley, J; Newell, E L; Harris, N; Clinch, J G; Lovell, C R

    2013-07-01

    Localized scleroderma is a rare but potentially disfiguring and disabling condition. Systemic treatment should be started early in those with active disease in key functional and cosmetic sites, but disease activity is difficult to determine clinically. Superficial blood flow has been shown to correlate with disease activity in localized scleroderma. To examine whether superficial blood flow measured by laser Doppler imaging (LDI) has the potential to predict disease progression and therefore select patients for early systemic treatment. A group of 20 individuals had clinical assessment and scanning LDI blood-flow measurements of 32 affected body sites. After a mean follow-up of 8.7 months their clinical outcome was compared with the results of the initial LDI assessment. Eleven out of 15 patients with an assessment of active LDI had progressed clinically, and 16 out of the 17 scans with inactive LDI assessment had not progressed, giving a positive predictive value of 73% and a negative predictive value of 94%. We believe that LDI can be a useful tool in predicting disease progression in localized scleroderma, and it may help clinicians to decide which patients to treat early. © 2013 The Authors BJD © 2013 British Association of Dermatologists.

  4. Fatigue Life Prediction of High Modulus Asphalt Concrete Based on the Local Stress-Strain Method

    Directory of Open Access Journals (Sweden)

    Mulian Zheng

    2017-03-01

    Full Text Available Previously published studies have proposed fatigue life prediction models for dense graded asphalt pavement based on flexural fatigue test. This study focused on the fatigue life prediction of High Modulus Asphalt Concrete (HMAC pavement using the local strain-stress method and direct tension fatigue test. First, the direct tension fatigue test at various strain levels was conducted on HMAC prism samples cut from plate specimens. Afterwards, their true stress-strain loop curves were obtained and modified to develop the strain-fatigue life equation. Then the nominal strain of HMAC course determined using finite element method was converted into local strain using the Neuber method. Finally, based on the established fatigue equation and converted local strain, a method to predict the pavement fatigue crack initiation life was proposed and the fatigue life of a typical HMAC overlay pavement which runs a risk of bottom-up cracking was predicted and validated. Results show that the proposed method was able to produce satisfactory crack initiation life.

  5. Spherical loudspeaker array for local active control of sound.

    Science.gov (United States)

    Rafaely, Boaz

    2009-05-01

    Active control of sound has been employed to reduce noise levels around listeners' head using destructive interference from noise-canceling sound sources. Recently, spherical loudspeaker arrays have been studied as multiple-channel sound sources, capable of generating sound fields with high complexity. In this paper, the potential use of a spherical loudspeaker array for local active control of sound is investigated. A theoretical analysis of the primary and secondary sound fields around a spherical sound source reveals that the natural quiet zones for the spherical source have a shell-shape. Using numerical optimization, quiet zones with other shapes are designed, showing potential for quiet zones with extents that are significantly larger than the well-known limit of a tenth of a wavelength for monopole sources. The paper presents several simulation examples showing quiet zones in various configurations.

  6. PLMPC - supervisor predictive control; PLMPC - controle supervisorio preditivo

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, Amalia Burger Santa Brigida; Matuck, Fuad Jorge [White Martins S.A., Rio de Janeiro, RJ (Brazil)

    2010-07-01

    MPC is the latest and most sophisticated technology for controlling chemical plants with several interactive variables. Since 1984, over 2000 MPC systems have been installed worldwide, mostly at oil refineries and large petrochemical facilities. Praxair was the first company to apply MPC technology to the air separation industry. MPC technology is now Praxair's standard platform for supervisory control of cryogenic air separation plants. Most new Praxair plants are controlled by MPC systems. The Pipeline MPC (PLMPC) drives at least 2 plants, A and B, GO2 production towards optimum targets during the pipeline variations. The purpose of the PLMPC is to optimize gas oxygen (GO2) production according to demand, while ensuring a quickly pipeline response. It is implemented using AspenTech DMCPlus software, which is configured with a model file and a controller configuration file, that executes periodically. (author)

  7. Rupture prediction for induction bends under opening mode bending with emphasis on strain localization

    International Nuclear Information System (INIS)

    Mitsuya, Masaki; Sakanoue, Takashi

    2015-01-01

    This study focuses on the opening mode of induction bends; this mode represents the deformation outside a bend. Bending experiments on induction bends are shown and the manner of failure of these bends was investigated. Ruptures occur at the intrados of the bends, which undergo tensile stress, and accompany the local reduction of wall thickness, i.e., necking that indicates strain localization. By implementing finite element analysis (FEA), it was shown that the rupture is dominated not by the fracture criterion of material but by the initiation of strain localization that is a deformation characteristic of the material. These ruptures are due to the rapid increase of local strain after the initiation of strain localization and suddenly reach the fracture criterion. For the evaluation of the deformability of the bends, a method based on FEA that can predict the displacement at the rupture is proposed. We show that the yield surface shape and the true stress–strain relationship after uniform elongation have to be defined on the basis of the actual properties of the bend material. The von Mises yield criterion, which is commonly used in cases of elastic–plastic FEA, could not predict the rupture and overestimated the deformability. In contrast, a yield surface obtained by performing tensile tests on a biaxial specimen could predict the rupture. The prediction of the rupture was accomplished by an inverse calibration method that determined the true stress-strain relationship after uniform elongation. As an alternative to the inverse calibration, a simple extrapolation method of the true stress-strain relationship after uniform elongation which can predict the rupture is proposed. - Highlights: • A method based on FEA that can predict the displacement at the rupture is proposed. • The yield surface shape and the true stress–strain have to be defined precisely. • The von Mises yield criterion overestimated the deformability. • The ruptures are due to the

  8. Wind turbine control with constraint handling: a model predictive control approach

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Hansen, Morten Hartvig; Poulsen, Niels Kjølstad

    2012-01-01

    on model predictive control, a control method well suited for constraint handling. The performance of the presented controller during an extreme operating gust is compared to that of a proportional-integral controller with integrator anti-windup. Furthermore, the presented controller-s capability...

  9. Edge localized modes control by resonant magnetic perturbations

    International Nuclear Information System (INIS)

    Nardon, E.

    2007-10-01

    The present work is dedicated to one of the most promising methods of control of the ELMs (Edge Localized Modes), based on a system of coils producing Resonant Magnetic Perturbations (RMPs). Our main objectives are, on the one hand, to improve the physical understanding of the mechanisms at play, and on the other hand to propose a concrete design of ELMs control coils for ITER. In order to calculate and analyze the magnetic perturbations produced by a given set of coils, we have developed the ERGOS code. The first ERGOS calculation was for the DIII-D ELMs control coils, the I-coils. It showed that they produce magnetic islands chains which overlap at the edge of the plasma, resulting in the ergodization of the magnetic field. We have then used ERGOS for the modelling of the experiments on ELMs control using the error field correction coils at JET and MAST. In the case of JET, we have shown the existence of a correlation between the mitigation of the ELMs and the ergodization of the magnetic field at the edge, in agreement with the DIII-D result. In order to design the ELMs control coils for ITER we have used ERGOS intensively, taking the case of the DIII-D I-coils as a reference. Three candidate designs came out, which we presented at the ITER Design Review, in 2007. Recently, the ITER management decided to provide a budget for building ELMs control coils, the design of which remains to be chosen between two of the three options that we proposed. Finally, in order to understand better the non-linear magnetohydrodynamics phenomena taking place in ELMs control by RMPs, we performed numerical simulations, in particular with the JOREK code for a DIII-D case. The simulations reveal the existence of convection cells induced at the edge by the magnetic perturbations, and the possible screening of the RMPs in presence of rotation

  10. Neural Network with Local Memory for Nuclear Reactor Power Level Control

    International Nuclear Information System (INIS)

    Uluyol, Oender; Ragheb, Magdi; Tsoukalas, Lefteri

    2001-01-01

    A methodology is introduced for a neural network with local memory called a multilayered local output gamma feedback (LOGF) neural network within the paradigm of locally-recurrent globally-feedforward neural networks. It appears to be well-suited for the identification, prediction, and control tasks in highly dynamic systems; it allows for the presentation of different timescales through incorporation of a gamma memory. A learning algorithm based on the backpropagation-through-time approach is derived. The spatial and temporal weights of the network are iteratively optimized for a given problem using the derived learning algorithm. As a demonstration of the methodology, it is applied to the task of power level control of a nuclear reactor at different fuel cycle conditions. The results demonstrate that the LOGF neural network controller outperforms the classical as well as the state feedback-assisted classical controllers for reactor power level control by showing a better tracking of the demand power, improving the fuel and exit temperature responses, and by performing robustly in different fuel cycle and power level conditions

  11. Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

    Science.gov (United States)

    Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

    2018-06-04

    Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing

  12. A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

    Science.gov (United States)

    Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

    2017-10-01

    This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

  13. Novel Approach for Prediction of Localized Necking in Case of Nonlinear Strain Paths

    Science.gov (United States)

    Drotleff, K.; Liewald, M.

    2017-09-01

    Rising customer expectations regarding design complexity and weight reduction of sheet metal components alongside with further reduced time to market implicate increased demand for process validation using numerical forming simulation. Formability prediction though often is still based on the forming limit diagram first presented in the 1960s. Despite many drawbacks in case of nonlinear strain paths and major advances in research in the recent years, the forming limit curve (FLC) is still one of the most commonly used criteria for assessing formability of sheet metal materials. Especially when forming complex part geometries nonlinear strain paths may occur, which cannot be predicted using the conventional FLC-Concept. In this paper a novel approach for calculation of FLCs for nonlinear strain paths is presented. Combining an interesting approach for prediction of FLC using tensile test data and IFU-FLC-Criterion a model for prediction of localized necking for nonlinear strain paths can be derived. Presented model is purely based on experimental tensile test data making it easy to calibrate for any given material. Resulting prediction of localized necking is validated using an experimental deep drawing specimen made of AA6014 material having a sheet thickness of 1.04 mm. The results are compared to IFU-FLC-Criterion based on data of pre-stretched Nakajima specimen.

  14. Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

    Science.gov (United States)

    Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

    2018-01-01

    The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

  15. Prediction of N2O emission from local information with Random Forest

    International Nuclear Information System (INIS)

    Philibert, Aurore; Loyce, Chantal; Makowski, David

    2013-01-01

    Nitrous oxide is a potent greenhouse gas, with a global warming potential 298 times greater than that of CO 2 . In agricultural soils, N 2 O emissions are influenced by a large number of environmental characteristics and crop management techniques that are not systematically reported in experiments. Random Forest (RF) is a machine learning method that can handle missing data and ranks input variables on the basis of their importance. We aimed to predict N 2 O emission on the basis of local information, to rank environmental and crop management variables according to their influence on N 2 O emission, and to compare the performances of RF with several regression models. RF outperformed the regression models for predictive purposes, and this approach led to the identification of three important input variables: N fertilization, type of crop, and experiment duration. This method could be used in the future for prediction of N 2 O emissions from local information. -- Highlights: ► Random Forest gave more accurate N 2 O predictions than regression. ► Missing data were well handled by Random Forest. ► The most important factors were nitrogen rate, type of crop and experiment duration. -- Random Forest, a machine learning method, outperformed the regression models for predicting N 2 O emissions and led to the identification of three important input variables

  16. A human genome-wide library of local phylogeny predictions for whole-genome inference problems

    Directory of Open Access Journals (Sweden)

    Schwartz Russell

    2008-08-01

    Full Text Available Abstract Background Many common inference problems in computational genetics depend on inferring aspects of the evolutionary history of a data set given a set of observed modern sequences. Detailed predictions of the full phylogenies are therefore of value in improving our ability to make further inferences about population history and sources of genetic variation. Making phylogenetic predictions on the scale needed for whole-genome analysis is, however, extremely computationally demanding. Results In order to facilitate phylogeny-based predictions on a genomic scale, we develop a library of maximum parsimony phylogenies within local regions spanning all autosomal human chromosomes based on Haplotype Map variation data. We demonstrate the utility of this library for population genetic inferences by examining a tree statistic we call 'imperfection,' which measures the reuse of variant sites within a phylogeny. This statistic is significantly predictive of recombination rate, shows additional regional and population-specific conservation, and allows us to identify outlier genes likely to have experienced unusual amounts of variation in recent human history. Conclusion Recent theoretical advances in algorithms for phylogenetic tree reconstruction have made it possible to perform large-scale inferences of local maximum parsimony phylogenies from single nucleotide polymorphism (SNP data. As results from the imperfection statistic demonstrate, phylogeny predictions encode substantial information useful for detecting genomic features and population history. This data set should serve as a platform for many kinds of inferences one may wish to make about human population history and genetic variation.

  17. Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

    Directory of Open Access Journals (Sweden)

    Ling Lu

    2016-12-01

    Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

  18. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1999-01-01

    This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....

  19. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Sichani, Mahdi Teimouri; Mirzaei, Mahmood

    2014-01-01

    by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement....... This approach is then taken into account and an MPC controller is designed for a model WEC and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

  20. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen N.; Sichani, Mahdi T.; Mirzaei, Mahmood

    2014-01-01

    by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement....... This approach is then taken into account and an MPC controller is designed for a model wave energy converter and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

  1. High speed, locally controlled data acquisition system for TFTR

    International Nuclear Information System (INIS)

    Feng, H.K.; Bradish, G.J.

    1983-01-01

    A high speed, locally controlled, data acquisition and transmission system has been developed by the CICADA (Central Instrumentation Control and Data Acquisition) Group for extracting certain timecritical data during a TFTR pulse and passing it to the control room, 1000 feet distant, to satisfy realtime requirements of frequently sampled variables. The system is designed to utilize any or all of the standard CAMAC (Computer Automated Measurement and Control) modules now employed on the CAMAC links for retrieval of the main body of data, but to operate them in a much faster manner than in a standard CAMAC system. To do this, a pre-programmable ROM sequencer is employed as a controller to transmit commands to the modules at intervals down to one microsecond, replacing the usual CAMAC dedicated computer, and increasing the command rate by an order of magnitude over what could be sent down a Branch Highway. Data coming from any number of channels originating within a single CAMAC ''crate'' is then time-multiplexed and transmitted over a single conductor pair in bi-phase at a 2.5 MHz bit rate using Manchester coding techniques. Benefits gained from this approach include: Reduction in the number of conductors required, elimination of line-to-line skew found in parallel transmission systems, and the capability of being transformer coupled or transmitted over a fiber optic cable to avoid safety hazards and ground loops. The main application for this system so far has been as the feedback path in this closed loop control of currents through the Tokamak's field coils. The paper will treat the system's various applications

  2. Predictive control, with restrictions for the climate of a greenhouse

    International Nuclear Information System (INIS)

    Pinon, Sandra; Pena, Miguel; Kuchen, Benjamin

    2002-01-01

    A proposal for controlling nonlinear systems under constraints is presented. a combination of model predictive control and feedback linearization is used. An alternative that uses extended kalman filter as non-measured variable estimator is applied for performing the constrained optimization. Finally, an observability analysis is done in closed loop in order to demonstrate observer convergence

  3. Neural networks for predictive control of the mechanism of ...

    African Journals Online (AJOL)

    In this paper, we are interested in the study of the control of orientation of a wind turbine like means of optimization of his output/input ratio (efficiency). The approach suggested is based on the neural predictive control which is justified by the randomness of the wind on the one hand, and on the other hand by the capacity of ...

  4. Neural Generalized Predictive Control of a non-linear Process

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability qu...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem.......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...

  5. Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan

    2012-01-01

    We study packetized predictive control, known to be robust against packet dropouts in networked systems. To obtain sparse packets for rate-limited networks, we design control packets via an ℓ0 optimization, which can be eectively solved by orthogonal matching pursuit. Our formulation ensures...

  6. Predicting worsening asthma control following the common cold

    NARCIS (Netherlands)

    Walter, M. J.; Castro, M.; Kunselman, S. J.; Chinchilli, V. M.; Reno, M.; Ramkumar, T. P.; Avila, P. C.; Boushey, H. A.; Ameredes, B. T.; Bleecker, E. R.; Calhoun, W. J.; Cherniack, R. M.; Craig, T. J.; Denlinger, L. C.; Israel, E.; Fahy, J. V.; Jarjour, N. N.; Kraft, M.; Lazarus, S. C.; Lemanske, R. F.; Martin, R. J.; Peters, S. P.; Ramsdell, J. W.; Sorkness, C. A.; Sutherland, E. R.; Szefler, S. J.; Wasserman, S. I.; Wechsler, M. E.

    2008-01-01

    The asthmatic response to the common cold is highly variable, and early characteristics that predict worsening of asthma control following a cold have not been identified. In this prospective multicentric cohort study of 413 adult subjects with asthma, the mini-Asthma Control Questionnaire

  7. Model Predictive Control for Offset-Free Reference Tracking

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav

    2016-01-01

    Roč. 5, č. 1 (2016), s. 8-13 ISSN 1805-3386 Institutional support: RVO:67985556 Keywords : offset-free reference tracking * predictive control * ARX model * state-space model * multi-input multi-output system * robotic system * mechatronic system Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2016/AS/belda-0458355.pdf

  8. Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

    Science.gov (United States)

    Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

    2016-12-01

    Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Neural Network Predictive Control for Vanadium Redox Flow Battery

    Directory of Open Access Journals (Sweden)

    Hai-Feng Shen

    2013-01-01

    Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.

  10. Modeling, Prediction, and Control of Heating Temperature for Tube Billet

    Directory of Open Access Journals (Sweden)

    Yachun Mao

    2015-01-01

    Full Text Available Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.

  11. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

    Science.gov (United States)

    Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

    2016-01-01

    A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

  13. Development of predictive control strategies for building climate control

    OpenAIRE

    NAGPAL, HIMANSHU

    2018-01-01

    APPROVED The rapid growth in energy usage and CO2 emissions has become a critical issue for the whole world. It is noteworthy that buildings are a major contributor to global primary energy consumption. Among building services, use of energy in heating-ventilation-air-conditioning (HVAC) system is particularly significant (about 50\\% of the total building energy consumption). Therefore, the development and implementation of effective control strategies to optimize the operation of HVAC sys...

  14. Predictive control and identification: Applications to steering dynamics

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela

    1996-01-01

    and of the loss function, which defines the optimality of the control. Some guidelines on how to choose the design parameters, depending on the type of process to be controlled and on the required control performance, are presented. A predictive track keeping system for a Mariner Class Vessel is formulated based...... the under- standing of the connection between identification and control, analysed in Chapter 7. Chapter 7 focuses on how to make the on-line identification for predictive control more robust towards unmodelled dynamics. The theory is verified via simulation studies on a Mariner Class Vessel. The effects...... and the need of a prefilter in the estimation are analysed and illustrated. Based on the idea that the control criterion must be dual to the estimation criterion, an iterative optimal prefilter is designed. This seems to be an appealing way to tune the model towards the objective for which the model...

  15. Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2017-10-01

    Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

  16. Catalytic cracking models developed for predictive control purposes

    Directory of Open Access Journals (Sweden)

    Dag Ljungqvist

    1993-04-01

    Full Text Available The paper deals with state-space modeling issues in the context of model-predictive control, with application to catalytic cracking. Emphasis is placed on model establishment, verification and online adjustment. Both the Fluid Catalytic Cracking (FCC and the Residual Catalytic Cracking (RCC units are discussed. Catalytic cracking units involve complex interactive processes which are difficult to operate and control in an economically optimal way. The strong nonlinearities of the FCC process mean that the control calculation should be based on a nonlinear model with the relevant constraints included. However, the model can be simple compared to the complexity of the catalytic cracking plant. Model validity is ensured by a robust online model adjustment strategy. Model-predictive control schemes based on linear convolution models have been successfully applied to the supervisory dynamic control of catalytic cracking units, and the control can be further improved by the SSPC scheme.

  17. Nonlinear Predictive Sliding Mode Control for Active Suspension System

    Directory of Open Access Journals (Sweden)

    Dazhuang Wang

    2018-01-01

    Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

  18. Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...

  19. Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

    Science.gov (United States)

    Gilra, Aditya; Gerstner, Wulfram

    2017-11-27

    The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

  20. Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

    Science.gov (United States)

    Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

    2014-02-01

    Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

  1. Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

    International Nuclear Information System (INIS)

    Rasam, A R A; Ghazali, R; Noor, A M M; Mohd, W M N W; Hamid, J R A; Bazlan, M J; Ahmad, N

    2014-01-01

    Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia

  2. Range-Space Predictive Control for Optimal Robot Motion

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef

    2008-01-01

    Roč. 1, č. 1 (2008), s. 1-7 ISSN 1998-0140 R&D Projects: GA ČR GP102/06/P275 Institutional research plan: CEZ:AV0Z10750506 Keywords : Accurate manipulation * Industrial robotics * Predictive control * Range-space control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0305644.pdf

  3. An adaptive predictive controller and its applications in power stations

    Energy Technology Data Exchange (ETDEWEB)

    Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

    1999-07-01

    Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

  4. Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

    KAUST Repository

    Domínguez, Luis F.

    2011-01-19

    In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.

  5. New approach to predict photoallergic potentials of chemicals based on murine local lymph node assay.

    Science.gov (United States)

    Maeda, Yosuke; Hirosaki, Haruka; Yamanaka, Hidenori; Takeyoshi, Masahiro

    2018-05-23

    Photoallergic dermatitis, caused by pharmaceuticals and other consumer products, is a very important issue in human health. However, S10 guidelines of the International Conference on Harmonization do not recommend the existing prediction methods for photoallergy because of their low predictability in human cases. We applied local lymph node assay (LLNA), a reliable, quantitative skin sensitization prediction test, to develop a new photoallergy prediction method. This method involves a three-step approach: (1) ultraviolet (UV) absorption analysis; (2) determination of no observed adverse effect level for skin phototoxicity based on LLNA; and (3) photoallergy evaluation based on LLNA. Photoallergic potential of chemicals was evaluated by comparing lymph node cell proliferation among groups treated with chemicals with minimal effect levels of skin sensitization and skin phototoxicity under UV irradiation (UV+) or non-UV irradiation (UV-). A case showing significant difference (P < .05) in lymph node cell proliferation rates between UV- and UV+ groups was considered positive for photoallergic reaction. After testing 13 chemicals, seven human photoallergens tested positive and the other six, with no evidence of causing photoallergic dermatitis or UV absorption, tested negative. Among these chemicals, both doxycycline hydrochloride and minocycline hydrochloride were tetracycline antibiotics with different photoallergic properties, and the new method clearly distinguished between the photoallergic properties of these chemicals. These findings suggested high predictability of our method; therefore, it is promising and effective in predicting human photoallergens. Copyright © 2018 John Wiley & Sons, Ltd.

  6. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  7. Rupture Predictions of Notched Ti-6Al-4V Using Local Approaches

    Directory of Open Access Journals (Sweden)

    Mirco Peron

    2018-04-01

    Full Text Available Ti-6Al-4V has been extensively used in structural applications in various engineering fields, from naval to automotive and from aerospace to biomedical. Structural applications are characterized by geometrical discontinuities such as notches, which are widely known to harmfully affect their tensile strength. In recent years, many attempts have been done to define solid criteria with which to reliably predict the tensile strength of materials. Among these criteria, two local approaches are worth mentioning due to the accuracy of their predictions, i.e., the strain energy density (SED approach and the theory of critical distance (TCD method. In this manuscript, the robustness of these two methods in predicting the tensile behavior of notched Ti-6Al-4V specimens has been compared. To this aim, two very dissimilar notch geometries have been tested, i.e., semi-circular and blunt V-notch with a notch root radius equal to 1 mm, and the experimental results have been compared with those predicted by the two models. The experimental values have been estimated with low discrepancies by either the SED approach and the TCD method, but the former results in better predictions. The deviations for the SED are in fact lower than 1.3%, while the TCD provides predictions with errors almost up to 8.5%. Finally, the weaknesses and the strengths of the two models have been reported.

  8. Controllable photon and phonon localization in optomechanical Lieb lattices.

    Science.gov (United States)

    Wan, Liang-Liang; Lü, Xin-You; Gao, Jin-Hua; Wu, Ying

    2017-07-24

    The Lieb lattice featuring flat band is not only important in strongly-correlated many-body physics, but also can be utilized to inspire new quantum devices. Here we propose an optomechanical Lieb lattice, where the flat-band physics of photon-phonon polaritons is demonstrated. The tunability of the band structure of the optomechanical arrays allows one to obtain an approximate photon or phonon flat band as well as the transition between them. This ultimately leads to the result that the controllable photon or phonon localization could be realized by the path interference effects. This study offers an alternative approach to explore the exotic photon and phonon many-body effects, which has potential applications in the future hybrid-photon-phonon quantum network and engineering new type solid-state quantum devices.

  9. Controlling Anderson localization in disordered photonic crystal waveguides

    DEFF Research Database (Denmark)

    Garcia-Fernández, David; Smolka, Stephan; Stobbe, Søren

    2010-01-01

    Quantum optics and quantum information technologies require enhancement of light-matter interaction by, for example, confining light in a small volume. A very recently demonstrated route towards light confinement makes use of multiple scattering of light and wave interference in disordered photonic...... structures [1,2]. Originally proposed for electrons by P. W. Anderson [3], only completely random systems without any long-range correlation between the scattering sites have been used so far, meaning that the Anderson-localized modes cannot be controlled. In disordered photonic crystals, these modes...... denoted by ng. By coupling light into a PCW with a tapered fiber (Fig. 1a), we have measured the ensemble-averaged exponential decay of the light distribution in the range 885 nm

  10. A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

    Science.gov (United States)

    Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

    2009-07-21

    Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

  11. Model Predictive Control for a Small Scale Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Jianfu Du

    2008-11-01

    Full Text Available Kinematical and dynamical equations of a small scale unmanned helicoper are presented in the paper. Based on these equations a model predictive control (MPC method is proposed for controlling the helicopter. This novel method allows the direct accounting for the existing time delays which are used to model the dynamics of actuators and aerodynamics of the main rotor. Also the limits of the actuators are taken into the considerations during the controller design. The proposed control algorithm was verified in real flight experiments where good perfomance was shown in postion control mode.

  12. Supervisory Model Predictive Control of the Heat Integrated Distillation Column

    DEFF Research Database (Denmark)

    Meyer, Kristian; Bisgaard, Thomas; Huusom, Jakob Kjøbsted

    2017-01-01

    This paper benchmarks a centralized control system based on model predictive control for the operation of the heat integrated distillation column (HIDiC) against a fully decentralized control system using the most complete column model currently available in the literature. The centralized control...... system outperforms the decentralized system, because it handles the interactions in the HIDiC process better. The integral absolute error (IAE) is reduced by a factor of 2 and a factor of 4 for control of the top and bottoms compositions, respectively....

  13. Prognostic nomograms for predicting survival and distant metastases in locally advanced rectal cancers.

    Directory of Open Access Journals (Sweden)

    Junjie Peng

    Full Text Available To develop prognostic nomograms for predicting outcomes in patients with locally advanced rectal cancers who do not receive preoperative treatment.A total of 883 patients with stage II-III rectal cancers were retrospectively collected from a single institution. Survival analyses were performed to assess each variable for overall survival (OS, local recurrence (LR and distant metastases (DM. Cox models were performed to develop a predictive model for each endpoint. The performance of model prediction was validated by cross validation and on an independent group of patients.The 5-year LR, DM and OS rates were 22.3%, 32.7% and 63.8%, respectively. Two prognostic nomograms were successfully developed to predict 5-year OS and DM-free survival rates, with c-index of 0.70 (95% CI = [0.66, 0.73] and 0.68 (95% CI = [0.64, 0.72] on the original dataset, and 0.76 (95% CI = [0.67, 0.86] and 0.73 (95% CI = [0.63, 0.83] on the validation dataset, respectively. Factors in our models included age, gender, carcinoembryonic antigen value, tumor location, T stage, N stage, metastatic lymph nodes ratio, adjuvant chemotherapy and chemoradiotherapy. Predicted by our nomogram, substantial variability in terms of 5-year OS and DM-free survival was observed within each TNM stage category.The prognostic nomograms integrated demographic and clinicopathological factors to account for tumor and patient heterogeneity, and thereby provided a more individualized outcome prognostication. Our individualized prediction nomograms could help patients with preoperatively under-staged rectal cancer about their postoperative treatment strategies and follow-up protocols.

  14. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm ...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.......Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...

  15. Enhanced pid vs model predictive control applied to bldc motor

    Science.gov (United States)

    Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

    2018-01-01

    BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

  16. Effective and Robust Generalized Predictive Speed Control of Induction Motor

    Directory of Open Access Journals (Sweden)

    Patxi Alkorta

    2013-01-01

    Full Text Available This paper presents and validates a new proposal for effective speed vector control of induction motors based on linear Generalized Predictive Control (GPC law. The presented GPC-PI cascade configuration simplifies the design with regard to GPC-GPC cascade configuration, maintaining the advantages of the predictive control algorithm. The robust stability of the closed loop system is demonstrated by the poles placement method for several typical cases of uncertainties in induction motors. The controller has been tested using several simulations and experiments and has been compared with Proportional Integral Derivative (PID and Sliding Mode (SM control schemes, obtaining outstanding results in speed tracking even in the presence of parameter uncertainties, unknown load disturbance, and measurement noise in the loop signals, suggesting its use in industrial applications.

  17. Modeling and Control of CSTR using Model based Neural Network Predictive Control

    OpenAIRE

    Shrivastava, Piyush

    2012-01-01

    This paper presents a predictive control strategy based on neural network model of the plant is applied to Continuous Stirred Tank Reactor (CSTR). This system is a highly nonlinear process; therefore, a nonlinear predictive method, e.g., neural network predictive control, can be a better match to govern the system dynamics. In the paper, the NN model and the way in which it can be used to predict the behavior of the CSTR process over a certain prediction horizon are described, and some commen...

  18. ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins

    Directory of Open Access Journals (Sweden)

    Raghava Gajendra PS

    2008-11-01

    Full Text Available Abstract Background The expansion of raw protein sequence databases in the post genomic era and availability of fresh annotated sequences for major localizations particularly motivated us to introduce a new improved version of our previously forged eukaryotic subcellular localizations prediction method namely "ESLpred". Since, subcellular localization of a protein offers essential clues about its functioning, hence, availability of localization predictor would definitely aid and expedite the protein deciphering studies. However, robustness of a predictor is highly dependent on the superiority of dataset and extracted protein attributes; hence, it becomes imperative to improve the performance of presently available method using latest dataset and crucial input features. Results Here, we describe augmentation in the prediction performance obtained for our most popular ESLpred method using new crucial features as an input to Support Vector Machine (SVM. In addition, recently available, highly non-redundant dataset encompassing three kingdoms specific protein sequence sets; 1198 fungi sequences, 2597 from animal and 491 plant sequences were also included in the present study. First, using the evolutionary information in the form of profile composition along with whole and N-terminal sequence composition as an input feature vector of 440 dimensions, overall accuracies of 72.7, 75.8 and 74.5% were achieved respectively after five-fold cross-validation. Further, enhancement in performance was observed when similarity search based results were coupled with whole and N-terminal sequence composition along with profile composition by yielding overall accuracies of 75.9, 80.8, 76.6% respectively; best accuracies reported till date on the same datasets. Conclusion These results provide confidence about the reliability and accurate prediction of SVM modules generated in the present study using sequence and profile compositions along with similarity search

  19. Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

    OpenAIRE

    Yi, Zhehan; Babqi, Abdulrahman J.; Wang, Yishen; Shi, Di; Etemadi, Amir H.; Wang, Zhiwei; Huang, Bibin

    2018-01-01

    Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining t...

  20. Prediction of welding residual distortions of large structures using a local/global approach

    International Nuclear Information System (INIS)

    Duan, Y. G.; Bergheau, J. M.; Vincent, Y.; Boitour, F.; Leblond, J. B.

    2007-01-01

    Prediction of welding residual distortions is more difficult than that of the microstructure and residual stresses. On the one hand, a fine mesh (often 3D) has to be used in the heat affected zone for the sake of the sharp variations of thermal, metallurgical and mechanical fields in this region. On the other hand, the whole structure is required to be meshed for the calculation of residual distortions. But for large structures, a 3D mesh is inconceivable caused by the costs of the calculation. Numerous methods have been developed to reduce the size of models. A local/global approach has been proposed to determine the welding residual distortions of large structures. The plastic strains and the microstructure due to welding are supposed can be determined from a local 3D model which concerns only the weld and its vicinity. They are projected as initial strains into a global 3D model which consists of the whole structure and obviously much less fine in the welded zone than the local model. The residual distortions are then calculated using a simple elastic analysis, which makes this method particularly effective in an industrial context. The aim of this article is to present the principle of the local/global approach then show the capacity of this method in an industrial context and finally study the definition of the local model

  1. A Robust Practical Generalized Predictive Control for BoilerSuper Heater Temperature Control

    OpenAIRE

    Zaki Maki Mohialdeen

    2015-01-01

    A practical method of robust generalized predictive controller (GPC) application is developed using a combination of Ziegler-Nichols type functions relating the GPC controller parameters to a first order with time delay process parameters and a model matching controller. The GPC controller and the model matching controller are used in a master/slave configuration, with the GPC as the master controller and the model matching controller as the slave controlle...

  2. Domestic appliances energy optimization with model predictive control

    International Nuclear Information System (INIS)

    Rodrigues, E.M.G.; Godina, R.; Pouresmaeil, E.; Ferreira, J.R.; Catalão, J.P.S.

    2017-01-01

    Highlights: • An alternative power management control for home appliances that require thermal regulation is presented. • A Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat. • Problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. • A modulation scheme of a two-level Model Predictive Control signal as an interface block is presented. • The implementation costs in home appliances with thermal regulation requirements are reduced. - Abstract: A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new

  3. Networked Predictive Control for Nonlinear Systems With Arbitrary Region Quantizers.

    Science.gov (United States)

    Yang, Hongjiu; Xu, Yang; Xia, Yuanqing; Zhang, Jinhui

    2017-04-06

    In this paper, networked predictive control is investigated for planar nonlinear systems with quantization by an extended state observer (ESO). The ESO is used not only to deal with nonlinear terms but also to generate predictive states for dealing with network-induced delays. Two arbitrary region quantizers are applied to take effective values of signals in forward channel and feedback channel, respectively. Based on a "zoom" strategy, sufficient conditions are given to guarantee stabilization of the closed-loop networked control system with quantization. A simulation example is proposed to exhibit advantages and availability of the results.

  4. Prediction-Based Control for Nonlinear Systems with Input Delay

    Directory of Open Access Journals (Sweden)

    I. Estrada-Sánchez

    2017-01-01

    Full Text Available This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state τ units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

  5. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  6. Generalized predictive control in the delta-domain

    DEFF Research Database (Denmark)

    Lauritsen, Morten Bach; Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad

    1995-01-01

    This paper describes new approaches to generalized predictive control formulated in the delta (δ) domain. A new δ-domain version of the continuous-time emulator-based predictor is presented. It produces the optimal estimate in the deterministic case whenever the predictor order is chosen greater...... than or equal to the number of future predicted samples, however a “good” estimate is usually obtained in a much longer range of samples. This is particularly advantageous at fast sampling rates where a “conventional” predictor is bound to become very computationally demanding. Two controllers...

  7. Local Prediction Models on Mid-Atlantic Ridge MORB by Principal Component Regression

    Science.gov (United States)

    Ling, X.; Snow, J. E.; Chin, W.

    2017-12-01

    The isotopic compositions of the daughter isotopes of long-lived radioactive systems (Sr, Nd, Hf and Pb ) can be used to map the scale and history of mantle heterogeneities beneath mid-ocean ridges. Our goal is to relate the multidimensional structure in the existing isotopic dataset with an underlying physical reality of mantle sources. The numerical technique of Principal Component Analysis is useful to reduce the linear dependence of the data to a minimum set of orthogonal eigenvectors encapsulating the information contained (cf Agranier et al 2005). The dataset used for this study covers almost all the MORBs along mid-Atlantic Ridge (MAR), from 54oS to 77oN and 8.8oW to -46.7oW, including replicating the dataset of Agranier et al., 2005 published plus 53 basalt samples dredged and analyzed since then (data from PetDB). The principal components PC1 and PC2 account for 61.56% and 29.21%, respectively, of the total isotope ratios variability. The samples with similar compositions to HIMU and EM and DM are identified to better understand the PCs. PC1 and PC2 are accountable for HIMU and EM whereas PC2 has limited control over the DM source. PC3 is more strongly controlled by the depleted mantle source than PC2. What this means is that all three principal components have a high degree of significance relevant to the established mantle sources. We also tested the relationship between mantle heterogeneity and sample locality. K-means clustering algorithm is a type of unsupervised learning to find groups in the data based on feature similarity. The PC factor scores of each sample are clustered into three groups. Cluster one and three are alternating on the north and south MAR. Cluster two exhibits on 45.18oN to 0.79oN and -27.9oW to -30.40oW alternating with cluster one. The ridge has been preliminarily divided into 16 sections considering both the clusters and ridge segments. The principal component regression models the section based on 6 isotope ratios and PCs. The

  8. Performance of local information-based link prediction: a sampling perspective

    Science.gov (United States)

    Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

    2012-08-01

    Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

  9. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    Science.gov (United States)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  10. REALIGNED MODEL PREDICTIVE CONTROL OF A PROPYLENE DISTILLATION COLUMN

    Directory of Open Access Journals (Sweden)

    A. I. Hinojosa

    Full Text Available Abstract In the process industry, advanced controllers usually aim at an economic objective, which usually requires closed-loop stability and constraints satisfaction. In this paper, the application of a MPC in the optimization structure of an industrial Propylene/Propane (PP splitter is tested with a controller based on a state space model, which is suitable for heavily disturbed environments. The simulation platform is based on the integration of the commercial dynamic simulator Dynsim® and the rigorous steady-state optimizer ROMeo® with the real-time facilities of Matlab. The predictive controller is the Infinite Horizon Model Predictive Control (IHMPC, based on a state-space model that that does not require the use of a state observer because the non-minimum state is built with the past inputs and outputs. The controller considers the existence of zone control of the outputs and optimizing targets for the inputs. We verify that the controller is efficient to control the propylene distillation system in a disturbed scenario when compared with a conventional controller based on a state observer. The simulation results show a good performance in terms of stability of the controller and rejection of large disturbances in the composition of the feed of the propylene distillation column.

  11. Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

    DEFF Research Database (Denmark)

    Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels

    1996-01-01

    Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local predicition of splice sites, is refin...

  12. Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

    Science.gov (United States)

    Wang, Ye; Ramirez-Jaime, Andres; Xu, Feng; Puig, Vicenç

    2017-01-01

    This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the effectiveness of the proposed strategy.

  13. Towards predictive control of extrusion weld seams: an integrated approach

    NARCIS (Netherlands)

    Bakker, A.J. den; Werkhoven, R.J.; Sillekens, W.H.; Katgerman, L.

    2010-01-01

    Longitudinal weld seams are an intrinsic feature in hollow extrusions produced with porthole dies. The formation of longitudinal weld seams is a solid bonding process, controlled by the local conditions in the extrusion die. Being the weakest areas within the extrusion cross section, it is desirable

  14. Stock return predictability and market integration: The role of global and local information

    Directory of Open Access Journals (Sweden)

    David G. McMillan

    2016-12-01

    Full Text Available This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on principal components analysis. Results identify three global expected returns factors, one related to the major stock markets of the US, UK and Asia and one related to the other markets analysed. The third component is related to dividend growth. A single dominant realised returns factor is also noted. A forecasting exercise comparing the principal components based factors to a US return factor and local market only factors, as well as the historical mean benchmark finds supportive evidence for the former approach. It is hoped that the results from this paper will be informative on three counts. First, to academics interested in understanding the dynamics asset price movement. Second, to market participants who aim to time the market and engage in portfolio and risk management. Third, to those (policy makers and others who are interested in linkages across international markets and the nature and degree of integration.

  15. Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

    Science.gov (United States)

    Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

    2010-09-01

    The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the

  16. Radiotherapy in desmoid tumors. Treatment response, local control, and analysis of local failures

    Energy Technology Data Exchange (ETDEWEB)

    Santti, Kirsi; Beule, Annette; Tuomikoski, Laura; Jaeaeskelaeinen, Anna-Stina; Saarilahti, Kauko; Tarkkanen, Maija; Blomqvist, Carl [Helsinki University Hospital and University of Helsinki, Comprehensive Cancer Center, Helsinki (Finland); Roenty, Mikko [HUSLAB and University of Helsinki, Department of Pathology, Helsinki (Finland); Ihalainen, Hanna [Helsinki University Hospital and University of Helsinki, Department of Plastic Surgery, Helsinki (Finland)

    2017-04-15

    Desmoid tumors (aggressive fibromatosis) are rare soft tissue tumors which frequently recur after surgery. Desmoid tumors arise from musculoaponeurotic tissue in the extremities, head and neck, abdominal wall, or intra-abdominally. Our aim was to examine the outcome of radiotherapy of desmoid tumors in a single institution series. We evaluated 41 patients with desmoid tumors treated with 49 radiotherapies between 1987 and 2012. Radiologic images for response evaluation were reassessed and responses to treatment registered according to RECIST criteria 1.1. For patients with local failures radiation dose distribution was determined in each local failure volume using image co-registration. Recurrences were classified as in-target, marginal, or out-of-target. Prognostic factors for radiotherapy treatment failure were evaluated. Radiotherapy doses varied from 20-63 Gy (median 50 Gy) with a median fraction size of 2 Gy. The objective response rate to definitive radiotherapy was 55% (12/22 patients). Median time to response was 14 months. A statistically significant dose-response relation for definitive and postoperative radiotherapy was observed both in univariate (p-value 0.002) and in multivariate analysis (p-value 0.02) adjusted for potential confounding factors. Surgery before radiotherapy or surgical margin had no significant effect on time to progression. Nine of 11 (82%) local failures were classified as marginal and two of 11 (18%) in-target. None of the recurrences occurred totally out-of-target. Radiotherapy is a valuable option for treating desmoid tumors. Radiotherapy dose appears to be significantly associated to local control. (orig.) [German] Desmoide (aggressive Fibromatosen) sind seltene Weichteiltumore der muskulaeren Membranen von Kopf, Hals, Extremitaeten und Bauchwand. Ziel war es, die Wirksamkeit der Strahlentherapie bei aggressiver Fibromatose an einer einzelnen Klinik zu untersuchen. Ausgewertet wurden 41 Patienten mit aggressiver Fibromatose, die

  17. Economic Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat and ...... and hereby shift the heat pump power consumption to periods with both low electricity prices and a high fraction of green energy in the grid.......Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat...

  18. Multimodel Predictive Control Approach for UAV Formation Flight

    Directory of Open Access Journals (Sweden)

    Chang-jian Ru

    2014-01-01

    Full Text Available Formation flight problem is the most important and interesting problem of multiple UAVs (unmanned aerial vehicles cooperative control. In this paper, a novel approach for UAV formation flight based on multimodel predictive control is designed. Firstly, the state equation of relative motion is obtained and then discretized. By the geometrical method, the characteristic points of state are determined. Afterwards, based on the linearization technique, the standard linear discrete model is obtained at each characteristic state point. Then, weighted model set is proposed using the idea of T-S (Takagi-Sugeno fuzzy control and the predictive control is carried out based on the multimodel method. Finally, to verify the performance of the proposed method, two different simulation scenarios are performed.

  19. Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

    Directory of Open Access Journals (Sweden)

    Wenbiao Li

    2016-04-01

    Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

  20. Integration of Predictive Display and Aircraft Flight Control System

    Directory of Open Access Journals (Sweden)

    Efremov A.V.

    2017-01-01

    Full Text Available The synthesis of predictive display information and direct lift control system are considered for the path control tracking tasks (in particular landing task. The both solutions are based on pilot-vehicle system analysis and requirements to provide the highest accuracy and lowest pilot workload. The investigation was carried out for cases with and without time delay in aircraft dynamics. The efficiency of the both ways for the flying qualities improvement and their integration is tested by ground based simulation.

  1. Predictors of Individual Tumor Local Control After Stereotactic Radiosurgery for Non-Small Cell Lung Cancer Brain Metastases

    International Nuclear Information System (INIS)

    Garsa, Adam A.; Badiyan, Shahed N.; DeWees, Todd; Simpson, Joseph R.; Huang, Jiayi; Drzymala, Robert E.; Barani, Igor J.; Dowling, Joshua L.; Rich, Keith M.; Chicoine, Michael R.; Kim, Albert H.; Leuthardt, Eric C.; Robinson, Clifford G.

    2014-01-01

    Purpose: To evaluate local control rates and predictors of individual tumor local control for brain metastases from non-small cell lung cancer (NSCLC) treated with stereotactic radiosurgery (SRS). Methods and Materials: Between June 1998 and May 2011, 401 brain metastases in 228 patients were treated with Gamma Knife single-fraction SRS. Local failure was defined as an increase in lesion size after SRS. Local control was estimated using the Kaplan-Meier method. The Cox proportional hazards model was used for univariate and multivariate analysis. Receiver operating characteristic analysis was used to identify an optimal cutpoint for conformality index relative to local control. A P value <.05 was considered statistically significant. Results: Median age was 60 years (range, 27-84 years). There were 66 cerebellar metastases (16%) and 335 supratentorial metastases (84%). The median prescription dose was 20 Gy (range, 14-24 Gy). Median overall survival from time of SRS was 12.1 months. The estimated local control at 12 months was 74%. On multivariate analysis, cerebellar location (hazard ratio [HR] 1.94, P=.009), larger tumor volume (HR 1.09, P<.001), and lower conformality (HR 0.700, P=.044) were significant independent predictors of local failure. Conformality index cutpoints of 1.4-1.9 were predictive of local control, whereas a cutpoint of 1.75 was the most predictive (P=.001). The adjusted Kaplan-Meier 1-year local control for conformality index ≥1.75 was 84% versus 69% for conformality index <1.75, controlling for tumor volume and location. The 1-year adjusted local control for cerebellar lesions was 60%, compared with 77% for supratentorial lesions, controlling for tumor volume and conformality index. Conclusions: Cerebellar tumor location, lower conformality index, and larger tumor volume were significant independent predictors of local failure after SRS for brain metastases from NSCLC. These results warrant further investigation in a prospective

  2. Generalized Predictive Control for Non-Stationary Systems

    DEFF Research Database (Denmark)

    Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen

    1994-01-01

    This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...

  3. Model Predictive Control of Mineral Column Flotation Process

    Directory of Open Access Journals (Sweden)

    Yahui Tian

    2018-06-01

    Full Text Available Column flotation is an efficient method commonly used in the mineral industry to separate useful minerals from ores of low grade and complex mineral composition. Its main purpose is to achieve maximum recovery while ensuring desired product grade. This work addresses a model predictive control design for a mineral column flotation process modeled by a set of nonlinear coupled heterodirectional hyperbolic partial differential equations (PDEs and ordinary differential equations (ODEs, which accounts for the interconnection of well-stirred regions represented by continuous stirred tank reactors (CSTRs and transport systems given by heterodirectional hyperbolic PDEs, with these two regions combined through the PDEs’ boundaries. The model predictive control considers both optimality of the process operations and naturally present input and state/output constraints. For the discrete controller design, spatially varying steady-state profiles are obtained by linearizing the coupled ODE–PDE model, and then the discrete system is obtained by using the Cayley–Tustin time discretization transformation without any spatial discretization and/or without model reduction. The model predictive controller is designed by solving an optimization problem with input and state/output constraints as well as input disturbance to minimize the objective function, which leads to an online-solvable finite constrained quadratic regulator problem. Finally, the controller performance to keep the output at the steady state within the constraint range is demonstrated by simulation studies, and it is concluded that the optimal control scheme presented in this work makes this flotation process more efficient.

  4. Prediction of active control of subsonic centrifugal compressor rotating stall

    Science.gov (United States)

    Lawless, Patrick B.; Fleeter, Sanford

    1993-01-01

    A mathematical model is developed to predict the suppression of rotating stall in a centrifugal compressor with a vaned diffuser. This model is based on the employment of a control vortical waveform generated upstream of the impeller inlet to damp weak potential disturbances that are the early stages of rotating stall. The control system is analyzed by matching the perturbation pressure in the compressor inlet and exit flow fields with a model for the unsteady behavior of the compressor. The model was effective at predicting the stalling behavior of the Purdue Low Speed Centrifugal Compressor for two distinctly different stall patterns. Predictions made for the effect of a controlled inlet vorticity wave on the stability of the compressor show that for minimum control wave magnitudes, on the order of the total inlet disturbance magnitude, significant damping of the instability can be achieved. For control waves of sufficient amplitude, the control phase angle appears to be the most important factor in maintaining a stable condition in the compressor.

  5. Model Predictive Control of the Hybrid Ventilation for Livestock

    DEFF Research Database (Denmark)

    Wu, Zhuang; Stoustrup, Jakob; Trangbæk, Klaus

    2006-01-01

    In this paper, design and simulation results of Model Predictive Control (MPC) strategy for livestock hybrid ventilation systems and associated indoor climate through variable valve openings and exhaust fans are presented. The design is based on thermal comfort parameters for poultry in barns...

  6. Predictive Models of Procedural Human Supervisory Control Behavior

    Science.gov (United States)

    2011-01-01

    821708, Brest , France. Page 139 of 150 Boussemart, Y. and M. L. Cummings (2010). "Predicting Supervisory Control Behavior with Hidden Markov Models...Strategies for Strike Planning. COGIS 2006 - Cognitive Systems with Interactive Sensors, Paris . Burges, C. (1998). "A Tutorial on Support Vector Machines

  7. Real-Time Optimization for Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Edlund, Kristian; Frison, Gianluca

    2012-01-01

    In this paper, we develop an efficient homogeneous and self-dual interior-point method for the linear programs arising in economic model predictive control. To exploit structure in the optimization problems, the algorithm employs a highly specialized Riccati iteration procedure. Simulations show...

  8. Model predictive control of hybrid systems : stability and robustness

    NARCIS (Netherlands)

    Lazar, M.

    2006-01-01

    This thesis considers the stabilization and the robust stabilization of certain classes of hybrid systems using model predictive control. Hybrid systems represent a broad class of dynamical systems in which discrete behavior (usually described by a finite state machine) and continuous behavior

  9. Stochastic Predictive Control of Multi-Microgrid Systems

    DEFF Research Database (Denmark)

    Bazmohammadi, Najmeh; Tahsiri, Ahmadreza; Anvari-Moghaddam, Amjad

    2018-01-01

    This paper presents a stochastic predictive control algorithm for a number of microgrids connected to the same distribution system. Each microgrid includes a variety of distributed resources such as wind turbine, photo voltaic units, energy storage devices and loads. Considering the uncertainty...

  10. Skill prediction of local weather forecasts based on the ECMWF ensemble

    Directory of Open Access Journals (Sweden)

    C. Ziehmann

    2001-01-01

    Full Text Available Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

  11. Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2016-12-02

    In the postgenomic era, the number of unreviewed protein sequences is remarkably larger and grows tremendously faster than that of reviewed ones. However, existing methods for protein subchloroplast localization often ignore the information from these unlabeled proteins. This paper proposes a multi-label predictor based on ensemble linear neighborhood propagation (LNP), namely, LNP-Chlo, which leverages hybrid sequence-based feature information from both labeled and unlabeled proteins for predicting localization of both single- and multi-label chloroplast proteins. Experimental results on a stringent benchmark dataset and a novel independent dataset suggest that LNP-Chlo performs at least 6% (absolute) better than state-of-the-art predictors. This paper also demonstrates that ensemble LNP significantly outperforms LNP based on individual features. For readers' convenience, the online Web server LNP-Chlo is freely available at http://bioinfo.eie.polyu.edu.hk/LNPChloServer/ .

  12. Contribution to the development of a Local Predictive Approach of the boiling crisis

    International Nuclear Information System (INIS)

    Montout, M.

    2009-01-01

    EDF aims at developing a 'Local Predictive Approach' of the boiling crisis for PWR core configurations, i.e. an approach resulting in (empirical) critical heat flux predictors based on local parameters provided by NEPTUNE-CFD code (for boiling bubbly flows, only in a first stage). Within this general framework, this PhD work consisted in assess one modelling of NEPTUNE-CFD code selected to simulate boiling bubble flows, then improve it. The latter objective led us to focus on the mechanistic modelling of subcooled nucleate boiling in forced convection. After a literature review, we identified physical improvements to be accounted for, especially with respect to bubble sliding phenomenon along the heated wall. Subsequently, we developed a force balance model in order to provide needed closure laws related to bubble detachment diameter from the nucleation site and lift-off bubble diameter from the wall. A new boiling model including such developments was eventually proposed, and preliminary assessed. (author)

  13. When predictions take control: The effect of task predictions on task switching performance

    Directory of Open Access Journals (Sweden)

    Wout eDuthoo

    2012-08-01

    Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

  14. ClubSub-P: Cluster-based subcellular localization prediction for Gram-negative bacteria and Archaea.

    Directory of Open Access Journals (Sweden)

    Nagarajan eParamasivam

    2011-11-01

    Full Text Available The subcellular localization of proteins provides important clues to their function in a cell. In our efforts to predict useful vaccine targets against Gram-negative bacteria, we noticed that misannotated start codons frequently lead to wrongly assigned subcellular localizations. This and other problems in subcellular localization prediction, such as the relatively high false positive and false negative rates of some tools, can be avoided by applying multiple prediction tools to groups of homologous proteins. Here we present ClubSub-P, an online database that combines existing subcellular localization prediction tools into a consensus pipeline from more than 600 proteomes of fully sequenced microorganisms. On top of the consensus prediction at the level of single sequences, the tool uses clusters of homologous proteins from Gram-negative bacteria and from Archaea to eliminate false positive and false negative predictions. ClubSub-P can assign the subcellular localization of proteins from Gram-negative bacteria and Archaea with high precision. The database is searchable, and can easily be expanded using either new bacterial genomes or new prediction tools as they become available. This will further improve the performance of the subcellular localization prediction, as well as the detection of misannotated start codons and other annotation errors. ClubSub-P is available online at http://toolkit.tuebingen.mpg.de/clubsubp/

  15. On prediction of inhibiting properties of o-aryl-carboxylates in local dissolution of iron

    International Nuclear Information System (INIS)

    Kuznetsov, Yu.I.; Kerbeleva, I.Ya.; Brusnikina, V.M.; Rozenfel'd, I.L.

    1979-01-01

    The anodic behaviour of Armco iron in the borate buffer (ph 7.4), containing sulphates as agressive anions and inhibiting substances - aryl carboxilates is studied. The possibility of using the principle of free energy linearity for quantitative prediction of protective properties of aryl carboxilates at the metal local solution is shown. The latter characterized by the pitting formation potential (phi sub(pf)), the inhibiting criterion being Δphi=phisub(pf)sup(R)-phisub(pf)sup(H). The linear correlation between Δphi and delta constants, reflecting the summary electron effects of substituent induction and mesomeric effects have been found

  16. Rate of PSA rise predicts metastatic versus local recurrence after definitive radiotherapy

    International Nuclear Information System (INIS)

    Sartor, C.I.; Strawderman, M.H.; Lin, X.; Kish, K.E.; McLaughlin, P.W.; Lichter, A.S.; Sandler, H.S.

    1995-01-01

    Objective: A rising PSA following treatment for adenocarcinoma of the prostate indicates eventual clinical failure, but the rate of rise can be quite different from patient to patient, as can the pattern of clinical failure. We sought to determine whether the rate of PSA rise could differentiate future local vs. metastatic failure. Materials and Methods: PSA values from our series of 671 patients treated between 1987 and 1994 with 3-D conformal radiotherapy for localized adenocarcinoma were analyzed. Patients who had a pre-treatment PSA and >4 post-treatment PSA values available, had received no hormonal therapy, and had information detailing clinical outcome were used in this analysis. First site of failure was determined by abnormal DRE or biopsy, abnormal bone scan or radiographic evidence of metastasis as directed by clinical symptoms or follow-up clinical exam. Each patient's PSA pattern was defined by the function PSA(t)=C 1 e - a 1 (t) + C 2 e a 2 (t) where -a 1 relates to the rate of decline and a 2 to the rate of rise, if any. Univariate analysis was used to determine the correlation between initial PSA or rising PSA and clinical failure. Adjacent category logistic regression analysis was used to analyze the rate of rise and pattern of clinical failure. Results: 671 patients were reviewed; 401 patients met the requirements and 2667 PSA values were analyzed. We confirmed the finding of others that pre-treatment PSA is a prognostic indicator: patients presenting with PSA 3-20ng/ml had a relative risk of 9 (p=0.03) and PSA>20ng/ml had a RR of 26 (p=0.002) for clinical failure when compared to presenting PSA 2 >1.5/year predicted metastatic as opposed to local failure when compared to PSA rise with a 2 between 0.5-1.5/yr or 1.5 log(ng/ml)/year vs. 0.5-1.5 log(ng/ml)/yr or <0.5 log(ng/ml)/yr. Conclusions: The rate of rise of PSA following definitive radiotherapy can predict clinical failure patterns, with a rapidly rising PSA indicating metastatic as opposed to

  17. Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

    Science.gov (United States)

    Gogol-Prokurat, Melanie

    2011-01-01

    If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

  18. Local control stations: Human engineering issues and insights

    International Nuclear Information System (INIS)

    Brown, W.S.; Higgins, J.C.; O'Hara, J.M.

    1994-09-01

    The objective of this research project was to evaluate current human engineering at local control stations (LCSs) in nuclear power plants, and to identify good human engineering practices relevant to the design of these operator interfaces. General literature and reports of operating experience were reviewed to determine the extent and type of human engineering deficiencies at LCSs in nuclear power plants. In-plant assessments were made of human engineering at single-function as well as multifunction LCSs. Besides confirming the existence of human engineering deficiencies at LCSs, the in-plant assessments provided information about the human engineering upgrades that have been made at nuclear power plants. Upgrades were typically the result of any of three influences regulatory activity, broad industry initiatives such as INPO, and specific in-plant programs (e.g. activities related to training). It is concluded that the quality of LCSs is quite variable and might be improved if there were greater awareness of good practices and existing human engineering guidance relevant to these operator interfaces, which is available from a variety of sources. To make such human engineering guidance more readily accessible, guidelines were compiled from such sources and included in the report as an appendix

  19. Prediction and control of rock burst of coal seam contacting gas in deep mining

    Energy Technology Data Exchange (ETDEWEB)

    En-yuan Wang; Xiao-fei Liu; En-lai Zhao; Zhen-tang Liu [China University of Mining and Technology, Xuzhou (China). School of Safety Engineering

    2009-06-15

    By analyzing the characteristics and the production mechanism of rock burst that goes with abnormal gas emission in deep coal seams, the essential method of eliminating abnormal gas emission by eliminating the occurrence of rock burst or depressing the magnitude of rock burst was considered. The No.237 working face in Nanshan coal mine was selected as the typical working face contacting gas in deep mining; aimed at this working face, a system of rock burst prediction and control for coal seam contacting gas in deep mining was established using the three-dimensional distinct element code software 3DEC. This system includes three parts: (1) regional prediction of rock burst hazard before mining; (2) local prediction of rock burst hazard during mining; and (3) rock burts control by an electromagnetic radiation method and specific drilling method. 8 refs., 4 figs., 1 tab.

  20. Fault-tolerant design of local controller for the poloidal field converter control system on ITER

    International Nuclear Information System (INIS)

    Shen, Jun; Fu, Peng; Gao, Ge; He, Shiying; Huang, Liansheng; Zhu, Lili; Chen, Xiaojiao

    2016-01-01

    Highlights: • The requirements on the Local Control Cubicles (LCC) for ITER Poloidal Field Converter are analyzed. • Decoupled service-based software architecture is proposed to make control loops on LCC running at varying cycle-time. • Fault detection and recovery methods for the LCC are developed to enhance the system. • The performance of the LCC with or without fault-tolerant feature is tested and compared. - Abstract: The control system for the Poloidal Field (PF) on ITER is a synchronously networked control system, which has several kinds of computational controllers. The Local Control Cubicles (LCC) play a critical role in the networked control system for they are the interface to all input and output signals. Thus, some additional work must be done to guarantee the LCCs proper operation under influence of faults. This paper mainly analyzes the system demands of the LCCs and faults which have been encountered recently. In order to handle these faults, decoupled service-based software architecture has been proposed. Based on this architecture, fault detection and system recovery methods, such as redundancy and rejuvenation, have been incorporated to achieve a fault-tolerant private network with the aid of QNX operating system. Unlike the conventional method, this method requires no additional hardware and can be achieved relatively easily. To demonstrate effectiveness the LCCs have been successfully tested during the recent PF Converter Unit performance tests for ITER.

  1. Fault-tolerant design of local controller for the poloidal field converter control system on ITER

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Jun; Fu, Peng; Gao, Ge; He, Shiying; Huang, Liansheng, E-mail: huangls@ipp.ac.cn; Zhu, Lili; Chen, Xiaojiao

    2016-11-15

    Highlights: • The requirements on the Local Control Cubicles (LCC) for ITER Poloidal Field Converter are analyzed. • Decoupled service-based software architecture is proposed to make control loops on LCC running at varying cycle-time. • Fault detection and recovery methods for the LCC are developed to enhance the system. • The performance of the LCC with or without fault-tolerant feature is tested and compared. - Abstract: The control system for the Poloidal Field (PF) on ITER is a synchronously networked control system, which has several kinds of computational controllers. The Local Control Cubicles (LCC) play a critical role in the networked control system for they are the interface to all input and output signals. Thus, some additional work must be done to guarantee the LCCs proper operation under influence of faults. This paper mainly analyzes the system demands of the LCCs and faults which have been encountered recently. In order to handle these faults, decoupled service-based software architecture has been proposed. Based on this architecture, fault detection and system recovery methods, such as redundancy and rejuvenation, have been incorporated to achieve a fault-tolerant private network with the aid of QNX operating system. Unlike the conventional method, this method requires no additional hardware and can be achieved relatively easily. To demonstrate effectiveness the LCCs have been successfully tested during the recent PF Converter Unit performance tests for ITER.

  2. Determining if pretreatment PSA doubling time predicts PSA trajectories after radiation therapy for localized prostate cancer

    International Nuclear Information System (INIS)

    Soto, Daniel E.; Andridge, Rebecca R.; Pan, Charlie C.; Williams, Scott G.; Taylor, Jeremy M.G.; Sandler, Howard M.

    2009-01-01

    Introduction: To determine if pretreatment PSA doubling time (PSA-DT) can predict post-radiation therapy (RT) PSA trajectories for localized prostate cancer. Materials and methods: Three hundred and seventy-five prostate cancer patients treated with external beam RT without androgen deprivation therapy (ADT) were identified with an adequate number of PSA values. We utilized a linear mixed model (LMM) analysis to model longitudinal PSA data sets after definitive treatment. Post-treatment PSA trajectories were allowed to depend on the pre-RT PSA-DT, pre-RT PSA (iPSA), Gleason score (GS), and T-stage. Results: Pre-RT PSA-DT had a borderline impact on predicting the rate of PSA rise after nadir (p = 0.08). For a typical low risk patient (T1, GS ≤ 6, iPSA 10), the predicted PSA-DT post-nadir was 21% shorter for pre-RT PSA-DT 24 month (19 month vs. 24 month). Additional significant predictors of post-RT PSA rate of rise included GS (p < 0.0001), iPSA (p < 0.0001), and T-stage (p = 0.02). Conclusions: We observed a trend between rapidly rising pre-RT PSA and the post-RT post-nadir PSA rise. This effect appeared to be independent of iPSA, GS, or T-stage. The results presented suggest that pretreatment PSA-DT may help predict post-RT PSA trajectories

  3. Economic Model Predictive Control for Spray Drying Plants

    DEFF Research Database (Denmark)

    Petersen, Lars Norbert

    and a complexity reduced control model is used for state estimation and prediction in the controllers. These models facilitate development and comparison of control strategies. We develop two MPC strategies; a linear tracking MPC with a Real-Time Optimization layer (MPC with RTO) and an Economic Nonlinear MPC (E...... horizon, out of which only the first input is applied to the dryer. This procedure is repeated at each sample instant and is solved numerically in real-time. The MPC with RTO tracks a target that optimizes the cost of operation at steady-state. The E-MPC optimizes the cost of operation directly by having...... this objective directly in the controller. The need for the RTO layer is then eliminated. We demonstrate the application of the proposed MPC with RTO to control an industrial GEA MSDTM-1250 spray dryer, which produces approximately 7500 kg/hr of enriched milk powder. Compared to the conventional PI controller...

  4. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  5. Composite control for raymond mill based on model predictive control and disturbance observer

    Directory of Open Access Journals (Sweden)

    Dan Niu

    2016-03-01

    Full Text Available In the raymond mill grinding process, precise control of operating load is vital for the high product quality. However, strong external disturbances, such as variations of ore size and ore hardness, usually cause great performance degradation. It is not easy to control the current of raymond mill constant. Several control strategies have been proposed. However, most of them (such as proportional–integral–derivative and model predictive control reject disturbances just through feedback regulation, which may lead to poor control performance in the presence of strong disturbances. For improving disturbance rejection, a control method based on model predictive control and disturbance observer is put forward in this article. The scheme employs disturbance observer as feedforward compensation and model predictive control controller as feedback regulation. The test results illustrate that compared with model predictive control method, the proposed disturbance observer–model predictive control method can obtain significant superiority in disturbance rejection, such as shorter settling time and smaller peak overshoot under strong disturbances.

  6. Frequency weighted model predictive control of wind turbine

    DEFF Research Database (Denmark)

    Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

    2013-01-01

    This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...

  7. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  8. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  9. Thermal Storage Power Balancing with Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2013-01-01

    The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination....... The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates...

  10. Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

    2013-01-01

    , we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based......The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...... on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point...

  11. Electric vehicle charge planning using Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels K.; Madsen, Henrik

    2012-01-01

    Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) are expected to play a large role in the future Smart Grid. They are expected to provide...... grid services, both for peak reduction and for ancillary services, by absorbing short term variations in the electricity production. In this paper the Economic MPC minimizes the cost of electricity consumption for a single EV. Simulations show savings of 50–60% of the electricity costs compared...... to uncontrolled charging from load shifting based on driving pattern predictions. The future energy system in Denmark will most likely be based on renewable energy sources e.g. wind and solar power. These green energy sources introduce stochastic fluctuations in the electricity production. Therefore, energy...

  12. Robust Model Predictive Control of a Wind Turbine

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

  13. Stability analysis of embedded nonlinear predictor neural generalized predictive controller

    Directory of Open Access Journals (Sweden)

    Hesham F. Abdel Ghaffar

    2014-03-01

    Full Text Available Nonlinear Predictor-Neural Generalized Predictive Controller (NGPC is one of the most advanced control techniques that are used with severe nonlinear processes. In this paper, a hybrid solution from NGPC and Internal Model Principle (IMP is implemented to stabilize nonlinear, non-minimum phase, variable dead time processes under high disturbance values over wide range of operation. Also, the superiority of NGPC over linear predictive controllers, like GPC, is proved for severe nonlinear processes over wide range of operation. The necessary conditions required to stabilize NGPC is derived using Lyapunov stability analysis for nonlinear processes. The NGPC stability conditions and improvement in disturbance suppression are verified by both simulation using Duffing’s nonlinear equation and real-time using continuous stirred tank reactor. Up to our knowledge, the paper offers the first hardware embedded Neural GPC which has been utilized to verify NGPC–IMP improvement in realtime.

  14. Economic model predictive control theory, formulations and chemical process applications

    CERN Document Server

    Ellis, Matthew; Christofides, Panagiotis D

    2017-01-01

    This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes. In addition to being...

  15. Predictive Control, Competitive Model Business Planning, and Innovation ERP

    DEFF Research Database (Denmark)

    Nourani, Cyrus F.; Lauth, Codrina

    2015-01-01

    is not viewed as the sum of its component elements, but the product of their interactions. The paper starts with introducing a systems approach to business modeling. A competitive business modeling technique, based on the author's planning techniques is applied. Systemic decisions are based on common......New optimality principles are put forth based on competitive model business planning. A Generalized MinMax local optimum dynamic programming algorithm is presented and applied to business model computing where predictive techniques can determine local optima. Based on a systems model an enterprise...... organizational goals, and as such business planning and resource assignments should strive to satisfy higher organizational goals. It is critical to understand how different decisions affect and influence one another. Here, a business planning example is presented where systems thinking technique, using Causal...

  16. Investigation for GOTHIC-3D prediction capability for the local hydrogen behavior analysis in the NPP containment

    International Nuclear Information System (INIS)

    Lee, Un-jang; Park, Goon-cherl

    2002-01-01

    Under a severe accident condition, hydrogen can be generated mainly from the reaction of zirconium cladding with hot steam and flammable hydrogen/air/steam mixtures can be formed. Thus hydrogen analysis is needed for a variety of reasons in the containment building; to predict the global containment response against the threat potential by hydrogen; to address certain safety issues such as the safety feature survivability due to global burning or explosion of hydrogen; or for designing and positioning of the hydrogen controller. In this study an analytical tool was used to predict the local hydrogen behavior in a small compartment and its analytical capability was examined through verification tests, which have been performed in SNU hydrogen mixing facilities. The analytical tool that was employed is the code GOTHIC which is a 3D three-fields (vapor, liquid and droplets) code specially developed for the containment analysis, and has the additional capability of modeling a number of different gases as well as air. The comparison between experimental and analytical tests results showed that the GOTHIC code is not applicable for the analysis of local hydrogen behavior in the highly transient condition and/or in small size compartment. (authors)

  17. One-Step-Ahead Predictive Control for Hydroturbine Governor

    Directory of Open Access Journals (Sweden)

    Zhihuai Xiao

    2015-01-01

    Full Text Available The hydroturbine generator regulating system can be considered as one system synthetically integrating water, machine, and electricity. It is a complex and nonlinear system, and its configuration and parameters are time-dependent. A one-step-ahead predictive control based on on-line trained neural networks (NNs for hydroturbine governor with variation in gate position is described in this paper. The proposed control algorithm consists of a one-step-ahead neuropredictor that tracks the dynamic characteristics of the plant and predicts its output and a neurocontroller to generate the optimal control signal. The weights of two NNs, initially trained off-line, are updated on-line according to the scalar error. The proposed controller can thus track operating conditions in real-time and produce the optimal control signal over the wide operating range. Only the inputs and outputs of the generator are measured and there is no need to determine the other states of the generator. Simulations have been performed with varying operating conditions and different disturbances to compare the performance of the proposed controller with that of a conventional PID controller and validate the feasibility of the proposed approach.

  18. Robust predictive control of a gasoline debutanizer column

    Directory of Open Access Journals (Sweden)

    E. Almeida Neto

    2000-12-01

    Full Text Available This paper studies the application of Model Predictive Control to moderately nonlinear processes. The system used in this work is an industrial gasoline debutanizer column. The paper presents two new formulations of MPC: MMPC (Multi-Model Predictive Controller and RSMPC (Robust Stable MPC. The approach is based on the concepts of Linear Matrix Inequalities (LMI, which have been recently introduced in the MPC field. Model uncertainty is considered by assuming that the true process model belongs to a convex set (polytope of possible plants. The controller has guaranteed stability when a Lyapunov type inequality constraint is included in the MPC problem. In the debutanizer column, several nonlinearities are present in the advanced control level when the manipulated inputs are the reflux flow and the reboiler heat duty. In most cases the controlled outputs are the contents of C5+ (pentane and heavier hydrocarbons in the LPG (Liquefied Petroleum Gas and the gasoline vapor pressure (P VR. In this case the QDMC algorithm which is usually applied to the debutanizer column has a poor performance and stability problems reflected in an oscillatory behavior of the process. The new approach considers several process models representing different operating conditions where linear models are identified. The results presented here show that the multimodel controller is capable of controlling the process in the entire operating window while the conventional MPC has a limited operating range.

  19. Pre- and post-radiotherapy computed tomography in laryngeal cancer: imaging-based prediction of local failure

    International Nuclear Information System (INIS)

    Pameijer, Frank A.; Hermans, Robert; Mancuso, Anthony A.; Mendenhall, William M.; Parsons, James T.; Stringer, Scott P.; Kubilis, Paul S.; Tinteren, Harm van

    1999-01-01

    Purpose: To determine if pre-radiotherapy (RT) and/or post-radiotherapy computed tomography (CT) can predict local failure in patients with laryngeal carcinoma treated with definitive RT. Methods and Materials: The pre- and post-RT CT examinations of 59 patients (T3 glottic carcinoma [n = 30] and T1-T4 supraglottic carcinoma [n = 29]) were reviewed. For each patient, the first post-RT CT study between 1 and 6 months after irradiation was used. All patients were treated with definitive hyperfractionated twice-daily continuous-course irradiation to a total dose of 6,720-7,920 cGy, and followed-up clinically for at least 2 years after completion of RT. Local control was defined as absence of primary tumor recurrence and a functioning larynx. On the pre-treatment CT study, each tumor was assigned a high-or low-risk profile for local failure after RT. The post-RT CT examinations were evaluated for post-treatment changes using a three-point post-RT CT-score: 1 = expected post-RT changes; 2 = focal mass with a maximal diameter of 1 cm, or < 50% estimated tumor volume reduction. Results: The local control rates at 2 years post-RT based on pre-treatment CT evaluation were 88% for low pre-treatment risk profile patients (95% CI: 66-96%) and 34% (95% CI: 19-50%) for high pre-treatment risk profile patients (risk ratio 6.583; 95% CI: 2.265-9.129; p = 0.0001). Based on post-treatment CT, the local control rates at 2 years post-RT were 94% for score 1, 67% for score 2, and 10% for score 3 (risk ratio 4.760; 95% CI: 2.278-9.950 p 0.0001). Post-RT CT scores added significant information to the pre-treatment risk profiles on prognosis. Conclusions: Pre-treatment CT risk profiles, as well as post-RT CT evaluation can identify patients, irradiated for laryngeal carcinomas, at high risk for developing local failure. When the post-RT CT score is available, it proves to be an even better prognosticator than the pre-treatment CT-risk profile

  20. Robust stability in predictive control with soft constraints

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2010-01-01

    In this paper we take advantage of the primary and dual Youla parameterizations for setting up a soft constrained model predictive control (MPC) scheme for which stability is guaranteed in face of norm-bounded uncertainties. Under special conditions guarantees are also given for hard input...... constraints. In more detail, we parameterize the MPC predictions in terms of the primary Youla parameter and use this parameter as the online optimization variable. The uncertainty is parameterized in terms of the dual Youla parameter. Stability can then be guaranteed through small gain arguments on the loop...

  1. Robust stability in constrained predictive control through the Youla parameterisations

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2011-01-01

    In this article we take advantage of the primary and dual Youla parameterisations to set up a soft constrained model predictive control (MPC) scheme. In this framework it is possible to guarantee stability in face of norm-bounded uncertainties. Under special conditions guarantees are also given...... for hard input constraints. In more detail, we parameterise the MPC predictions in terms of the primary Youla parameter and use this parameter as the on-line optimisation variable. The uncertainty is parameterised in terms of the dual Youla parameter. Stability can then be guaranteed through small gain...

  2. High level model predictive control for plug-and-play process control with stability guaranty

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob

    2010-01-01

    In this paper a method for designing a stabilizing high level model predictive controller for a hierarchical plug- and-play process is presented. This is achieved by abstracting the lower layers of the controller structure as low order models with uncertainty and by using a robust model predictive...... controller for generating the references for these. A simulation example, in which the actuators in a process control system are changed, is reported to show the potential of this approach for plug and play process control....

  3. Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

    Directory of Open Access Journals (Sweden)

    Jun Wang

    2017-11-01

    Full Text Available Protein-protein interactions (PPIs play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs and a novel local conjoint triad description (LCTD feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.

  4. Force Control for a Pneumatic Cylinder Using Generalized Predictive Controller Approach

    OpenAIRE

    Mohd Faudzi, Ahmad ’Athif; Mustafa, Nu’man Din; Osman, Khairuddin

    2014-01-01

    Pneumatic cylinder is a well-known device because of its high power to weight ratio, easy use, and environmental safety. Pneumatic cylinder uses air as its power source and converts it to a possible movement such as linear and rotary movement. In order to control the pneumatic cylinder, controller algorithm is needed to control the on-off solenoid valve with encoder and pressure sensor as the feedback inputs. In this paper, generalized predictive controller (GPC) is proposed as the control st...

  5. Optimal Local Dimming for LC Image Formation With Controllable Backlighting

    DEFF Research Database (Denmark)

    Shu, Xiao; Wu, Xiaolin; Forchhammer, Søren

    2013-01-01

    Light emitting diode (LED)-backlit liquid crystal displays (LCDs) hold the promise of improving image quality while reducing the energy consumption with signal-dependent local dimming. However, most existing local dimming algorithms are mostly motivated by simple implementation, and they often la...

  6. Model predictive control of room temperature with disturbance compensation

    Science.gov (United States)

    Kurilla, Jozef; Hubinský, Peter

    2017-08-01

    This paper deals with temperature control of multivariable system of office building. The system is simplified to several single input-single output systems by decoupling their mutual linkages, which are separately controlled by regulator based on generalized model predictive control. Main part of this paper focuses on the accuracy of the office temperature with respect to occupancy profile and effect of disturbance. Shifting of desired temperature and changing of weighting coefficients are used to achieve the desired accuracy of regulation. The final structure of regulation joins advantages of distributed computing power and possibility to use network communication between individual controllers to consider the constraints. The advantage of using decoupled MPC controllers compared to conventional PID regulators is demonstrated in a simulation study.

  7. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    Science.gov (United States)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  8. Low trait self-control predicts self-handicapping.

    Science.gov (United States)

    Uysal, Ahmet; Knee, C Raymond

    2012-02-01

    Past research has shown that self-handicapping stems from uncertainty about one's ability and self-presentational concerns. The present studies suggest that low dispositional self-control is also associated with self-handicapping. In 3 studies (N = 289), the association between self-control and self-handicapping was tested. Self-control was operationalized as trait self-control, whereas self-handicapping was operationalized as trait self-handicapping in Study 1 (N = 160), self-reported self-handicapping in Study 2 (N = 74), and behavioral self-handicapping in Study 3 (N = 55). In all 3 studies, hierarchical regression analyses revealed that low self-control predicts self-handicapping, independent of self-esteem, self-doubt, social desirability, and gender. © 2012 The Authors. Journal of Personality © 2012, Wiley Periodicals, Inc.

  9. Health-aware Model Predictive Control of Pasteurization Plant

    Science.gov (United States)

    Karimi Pour, Fatemeh; Puig, Vicenç; Ocampo-Martinez, Carlos

    2017-01-01

    In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.

  10. A LIDAR-assisted model predictive controller added on a traditional wind turbine controller

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Hansen, Morten Hartvig

    2016-01-01

    control and opens the market of retrofitting existing wind turbines with the new technology. In this paper, we suggest a model predictive controller (MPC) that is added to the basic gain scheduled PI controller of a WT to enhance the performance of the closed loop system using LIDAR measurements...

  11. Supervisor localization a top-down approach to distributed control of discrete-event systems

    CERN Document Server

    Cai, Kai

    2016-01-01

    This monograph presents a systematic top-down approach to distributed control synthesis of discrete-event systems (DES). The approach is called supervisor localization; its essence is the allocation of external supervisory control action to individual component agents as their internal control strategies. The procedure is: first synthesize a monolithic supervisor, to achieve globally optimal and nonblocking controlled behavior, then decompose the monolithic supervisor into local controllers, one for each agent. The collective behavior of the resulting local controllers is identical to that achieved by the monolithic supervisor. The basic localization theory is first presented in the Ramadge–Wonham language-based supervisory control framework, then demonstrated with distributed control examples of multi-robot formations, manufacturing systems, and distributed algorithms. An architectural approach is adopted to apply localization to large-scale DES; this yields a heterarchical localization procedure, which is...

  12. Can Image-Defined Risk Factors Predict Surgical Complications in Localized Neuroblastoma?

    Science.gov (United States)

    Yoneda, Akihiro; Nishikawa, Masanori; Uehara, Shuichiro; Oue, Takaharu; Usui, Noriaki; Inoue, Masami; Fukuzawa, Masahiro; Okuyama, Hiroomi

    2016-02-01

    Image-defined risk factors (IDRFs) have been propounded for predicting the surgical risks associated with localized neuroblastoma (NB) since 2009. In 2011, a new guideline (NG) for assessing IDRFs was published. According to the NG, the situation in which "the tumor is only in contact with renal vessels," should be considered to be "IDRF-present." Previously, this situation was diagnosed as "IDRF absent." In this study, we evaluated the IDRFs in localized NB patients to clarify the predictive capability of IDRFs for surgical complications, as well as the usefulness of the NG. Materials and A total of 107 localized patients with NB were included in this study. The enhanced computed tomography and magnetic resonance images from the time of their diagnoses were evaluated by a single radiologist. We also analyzed the association of clinical factors, including the IDRFs (before and after applying the NG), with surgical complications. Of the 107 patients, 33 and 74 patients were diagnosed as IDRF-present (OP group), and IDRF-absent (ON group) before the NG, respectively. According to the NG, there were 76 and 31 patients who were classified as IDRF-present (NP group) and IDRF absent (NN group), respectively. Thus, 43 (40%) patients in the ON group were reassigned to the NP group after the NG. Surgical complications were observed in 17 of 82 patients who underwent surgical resection. Of the patients who underwent secondary operations, surgical complication rates were 55% in the OP group and 44% in the NP group. According to a univariate analysis, non-INSS 1, IDRFs before and after the NG and secondary operations were significantly associated with surgical complications. In a multivariate analysis, non-INSS 1 status and IDRFs after the NG were significantly associated with surgical complications. Georg Thieme Verlag KG Stuttgart · New York.

  13. Predicting CT Image From MRI Data Through Feature Matching With Learned Nonlinear Local Descriptors.

    Science.gov (United States)

    Yang, Wei; Zhong, Liming; Chen, Yang; Lin, Liyan; Lu, Zhentai; Liu, Shupeng; Wu, Yao; Feng, Qianjin; Chen, Wufan

    2018-04-01

    Attenuation correction for positron-emission tomography (PET)/magnetic resonance (MR) hybrid imaging systems and dose planning for MR-based radiation therapy remain challenging due to insufficient high-energy photon attenuation information. We present a novel approach that uses the learned nonlinear local descriptors and feature matching to predict pseudo computed tomography (pCT) images from T1-weighted and T2-weighted magnetic resonance imaging (MRI) data. The nonlinear local descriptors are obtained by projecting the linear descriptors into the nonlinear high-dimensional space using an explicit feature map and low-rank approximation with supervised manifold regularization. The nearest neighbors of each local descriptor in the input MR images are searched in a constrained spatial range of the MR images among the training dataset. Then the pCT patches are estimated through k-nearest neighbor regression. The proposed method for pCT prediction is quantitatively analyzed on a dataset consisting of paired brain MRI and CT images from 13 subjects. Our method generates pCT images with a mean absolute error (MAE) of 75.25 ± 18.05 Hounsfield units, a peak signal-to-noise ratio of 30.87 ± 1.15 dB, a relative MAE of 1.56 ± 0.5% in PET attenuation correction, and a dose relative structure volume difference of 0.055 ± 0.107% in , as compared with true CT. The experimental results also show that our method outperforms four state-of-the-art methods.

  14. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  15. Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

    KAUST Repository

    Siddiqui, Bilal A.; El-Ferik, Sami; Abdelkader, Mohamed

    2016-01-01

    In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

  16. Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

    KAUST Repository

    Siddiqui, Bilal A.

    2016-07-26

    In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

  17. Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China.

    Directory of Open Access Journals (Sweden)

    Zhihao Li

    2017-03-01

    Full Text Available Dengue fever (DF in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data.A Dengue Baidu Search Index (DBSI was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM with or without DBSI were established. The generalized cross validation (GCV score and deviance explained indexes, intraclass correlation coefficient (ICC and root mean squared error (RMSE, were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86 has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29.Our study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou.

  18. Prediction of essential proteins based on subcellular localization and gene expression correlation.

    Science.gov (United States)

    Fan, Yetian; Tang, Xiwei; Hu, Xiaohua; Wu, Wei; Ping, Qing

    2017-12-01

    Essential proteins are indispensable to the survival and development process of living organisms. To understand the functional mechanisms of essential proteins, which can be applied to the analysis of disease and design of drugs, it is important to identify essential proteins from a set of proteins first. As traditional experimental methods designed to test out essential proteins are usually expensive and laborious, computational methods, which utilize biological and topological features of proteins, have attracted more attention in recent years. Protein-protein interaction networks, together with other biological data, have been explored to improve the performance of essential protein prediction. The proposed method SCP is evaluated on Saccharomyces cerevisiae datasets and compared with five other methods. The results show that our method SCP outperforms the other five methods in terms of accuracy of essential protein prediction. In this paper, we propose a novel algorithm named SCP, which combines the ranking by a modified PageRank algorithm based on subcellular compartments information, with the ranking by Pearson correlation coefficient (PCC) calculated from gene expression data. Experiments show that subcellular localization information is promising in boosting essential protein prediction.

  19. NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

    Directory of Open Access Journals (Sweden)

    Provart Nicholas

    2009-06-01

    Full Text Available Abstract Background Nuclear localization signals (NLSs are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood. Results In this paper, we present an analysis of characterized NLSs in yeast, and find, despite the large number of nuclear import pathways, that NLSs seem to show similar patterns of amino acid residues. We test current prediction methods and observe a low true positive rate. We therefore suggest an approach using hidden Markov models (HMMs to predict novel NLSs in proteins. We show that our method is able to consistently find 37% of the NLSs with a low false positive rate and that our method retains its true positive rate outside of the yeast data set used for the training parameters. Conclusion Our implementation of this model, NLStradamus, is made available at: http://www.moseslab.csb.utoronto.ca/NLStradamus/

  20. Predictive model for local scour downstream of hydrokinetic turbines in erodible channels

    Science.gov (United States)

    Musa, Mirko; Heisel, Michael; Guala, Michele

    2018-02-01

    A modeling framework is derived to predict the scour induced by marine hydrokinetic turbines installed on fluvial or tidal erodible bed surfaces. Following recent advances in bridge scour formulation, the phenomenological theory of turbulence is applied to describe the flow structures that dictate the equilibrium scour depth condition at the turbine base. Using scaling arguments, we link the turbine operating conditions to the flow structures and scour depth through the drag force exerted by the device on the flow. The resulting theoretical model predicts scour depth using dimensionless parameters and considers two potential scenarios depending on the proximity of the turbine rotor to the erodible bed. The model is validated at the laboratory scale with experimental data comprising the two sediment mobility regimes (clear water and live bed), different turbine configurations, hydraulic settings, bed material compositions, and migrating bedform types. The present work provides future developers of flow energy conversion technologies with a physics-based predictive formula for local scour depth beneficial to feasibility studies and anchoring system design. A potential prototype-scale deployment in a large sandy river is also considered with our model to quantify how the expected scour depth varies as a function of the flow discharge and rotor diameter.

  1. Model predictive control of a wind turbine modelled in Simpack

    International Nuclear Information System (INIS)

    Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

    2014-01-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

  2. Model predictive control of a wind turbine modelled in Simpack

    Science.gov (United States)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  3. Computationally efficient model predictive control algorithms a neural network approach

    CERN Document Server

    Ławryńczuk, Maciej

    2014-01-01

    This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: ·         A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. ·         Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. ·         The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). ·         The MPC algorithms with neural approximation with no on-line linearization. ·         The MPC algorithms with guaranteed stability and robustness. ·         Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...

  4. Distributed predictive control of spiral wave in cardiac excitable media

    International Nuclear Information System (INIS)

    Zheng-Ning, Gan; Xin-Ming, Cheng

    2010-01-01

    In this paper, we propose the distributed predictive control strategies of spiral wave in cardiac excitable media. The modified FitzHugh–Nagumo model was used to express the cardiac excitable media approximately. Based on the control-Lyapunov theory, we obtained the distributed control equation, which consists of a positive control-Lyapunov function and a positive cost function. Using the equation, we investigate two kinds of robust control strategies: the time-dependent distributed control strategy and the space-time dependent distributed control strategy. The feasibility of the strategies was demonstrated via an illustrative example, in which the spiral wave was prevented to occur, and the possibility for inducing ventricular fibrillation was eliminated. The strategies are helpful in designing various cardiac devices. Since the second strategy is more efficient and robust than the first one, and the response time in the second strategy is far less than that in the first one, the former is suitable for the quick-response control systems. In addition, our spatiotemporal control strategies, especially the second strategy, can be applied to other cardiac models, even to other reaction-diffusion systems. (general)

  5. Water hammer prediction and control: the Green's function method

    Science.gov (United States)

    Xuan, Li-Jun; Mao, Feng; Wu, Jie-Zhi

    2012-04-01

    By Green's function method we show that the water hammer (WH) can be analytically predicted for both laminar and turbulent flows (for the latter, with an eddy viscosity depending solely on the space coordinates), and thus its hazardous effect can be rationally controlled and minimized. To this end, we generalize a laminar water hammer equation of Wang et al. (J. Hydrodynamics, B2, 51, 1995) to include arbitrary initial condition and variable viscosity, and obtain its solution by Green's function method. The predicted characteristic WH behaviors by the solutions are in excellent agreement with both direct numerical simulation of the original governing equations and, by adjusting the eddy viscosity coefficient, experimentally measured turbulent flow data. Optimal WH control principle is thereby constructed and demonstrated.

  6. Finite element predictions of active buckling control of stiffened panels

    Science.gov (United States)

    Thompson, Danniella M.; Griffin, O. H., Jr.

    1993-04-01

    Materials systems and structures that can respond 'intelligently' to their environment are currently being proposed and investigated. A series of finite element analyses was performed to investigate the potential for active buckling control of two different stiffened panels by embedded shape memory alloy (SMA) rods. Changes in the predicted buckling load increased with the magnitude of the actuation level for a given structural concept. Increasing the number of actuators for a given concept yielded greater predicted increases in buckling load. Considerable control authority was generated with a small number of actuators, with greater authority demonstrated for those structural concepts where the activated SMA rods could develop greater forces and moments on the structure. Relatively simple and inexpensive analyses were performed with standard finite elements to determine such information, indicating the viability of these types of models for design purposes.

  7. Interpreting Disruption Prediction Models to Improve Plasma Control

    Science.gov (United States)

    Parsons, Matthew

    2017-10-01

    In order for the tokamak to be a feasible design for a fusion reactor, it is necessary to minimize damage to the machine caused by plasma disruptions. Accurately predicting disruptions is a critical capability for triggering any mitigative actions, and a modest amount of attention has been given to efforts that employ machine learning techniques to make these predictions. By monitoring diagnostic signals during a discharge, such predictive models look for signs that the plasma is about to disrupt. Typically these predictive models are interpreted simply to give a `yes' or `no' response as to whether a disruption is approaching. However, it is possible to extract further information from these models to indicate which input signals are more strongly correlated with the plasma approaching a disruption. If highly accurate predictive models can be developed, this information could be used in plasma control schemes to make better decisions about disruption avoidance. This work was supported by a Grant from the 2016-2017 Fulbright U.S. Student Program, administered by the Franco-American Fulbright Commission in France.

  8. Psychological Factors Predict Local and Referred Experimental Muscle Pain: A Cluster Analysis in Healthy Adults

    Science.gov (United States)

    Lee, Jennifer E.; Watson, David; Frey-Law, Laura A.

    2012-01-01

    Background Recent studies suggest an underlying three- or four-factor structure explains the conceptual overlap and distinctiveness of several negative emotionality and pain-related constructs. However, the validity of these latent factors for predicting pain has not been examined. Methods A cohort of 189 (99F; 90M) healthy volunteers completed eight self-report negative emotionality and pain-related measures (Eysenck Personality Questionnaire-Revised; Positive and Negative Affect Schedule; State-Trait Anxiety Inventory; Pain Catastrophizing Scale; Fear of Pain Questionnaire; Somatosensory Amplification Scale; Anxiety Sensitivity Index; Whiteley Index). Using principal axis factoring, three primary latent factors were extracted: General Distress; Catastrophic Thinking; and Pain-Related Fear. Using these factors, individuals clustered into three subgroups of high, moderate, and low negative emotionality responses. Experimental pain was induced via intramuscular acidic infusion into the anterior tibialis muscle, producing local (infusion site) and/or referred (anterior ankle) pain and hyperalgesia. Results Pain outcomes differed between clusters (multivariate analysis of variance and multinomial regression), with individuals in the highest negative emotionality cluster reporting the greatest local pain (p = 0.05), mechanical hyperalgesia (pressure pain thresholds; p = 0.009) and greater odds (2.21 OR) of experiencing referred pain compared to the lowest negative emotionality cluster. Conclusion Our results provide support for three latent psychological factors explaining the majority of the variance between several pain-related psychological measures, and that individuals in the high negative emotionality subgroup are at increased risk for (1) acute local muscle pain; (2) local hyperalgesia; and (3) referred pain using a standardized nociceptive input. PMID:23165778

  9. A six-gene signature predicts survival of patients with localized pancreatic ductal adenocarcinoma.

    Directory of Open Access Journals (Sweden)

    Jeran K Stratford

    2010-07-01

    Full Text Available Pancreatic ductal adenocarcinoma (PDAC remains a lethal disease. For patients with localized PDAC, surgery is the best option, but with a median survival of less than 2 years and a difficult and prolonged postoperative course for most, there is an urgent need to better identify patients who have the most aggressive disease.We analyzed the gene expression profiles of primary tumors from patients with localized compared to metastatic disease and identified a six-gene signature associated with metastatic disease. We evaluated the prognostic potential of this signature in a training set of 34 patients with localized and resected PDAC and selected a cut-point associated with outcome using X-tile. We then applied this cut-point to an independent test set of 67 patients with localized and resected PDAC and found that our signature was independently predictive of survival and superior to established clinical prognostic factors such as grade, tumor size, and nodal status, with a hazard ratio of 4.1 (95% confidence interval [CI] 1.7-10.0. Patients defined to be high-risk patients by the six-gene signature had a 1-year survival rate of 55% compared to 91% in the low-risk group.Our six-gene signature may be used to better stage PDAC patients and assist in the difficult treatment decisions of surgery and to select patients whose tumor biology may benefit most from neoadjuvant therapy. The use of this six-gene signature should be investigated in prospective patient cohorts, and if confirmed, in future PDAC clinical trials, its potential as a biomarker should be investigated. Genes in this signature, or the pathways that they fall into, may represent new therapeutic targets. Please see later in the article for the Editors' Summary.

  10. Stochastic Model Predictive Control with Applications in Smart Energy Systems

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Edlund, Kristian; Mølbak, Tommy

    2012-01-01

    to cover more than 50% of the total consumption by 2050. Energy systems based on significant amounts of renewable energy sources are subject to uncertainties. To accommodate the need for model predictive control (MPC) of such systems, the effect of the stochastic effects on the constraints must...... study, we consider a system consisting of fuel-fired thermal power plants, wind farms and electric vehicles....

  11. Predictability of solute transport in diffusion-controlled hydrogeologic regimes

    International Nuclear Information System (INIS)

    Gillham, R.W.; Cherry, J.A.

    1983-01-01

    Hydrogeologic regimes that are favourable for the subsurface management of low-level radioactive wastes must have transport properties that will limit the migration velocity of contaminants to some acceptably low value. Of equal importance, for the purpose of impact assessment and licensing, is the need to be able to predict, with a reasonable degree of certainty and over long time periods, what the migration velocity of the various contaminants of interest will be. This paper presents arguments to show that in addition to having favourable velocity characteristics, transport in saturated, diffusion-controlled hydrogeologic regimes is considerably more predictable than in the most common alternatives. The classical transport models for unsaturated, saturated-advection-controlled and saturated-diffusion-controlled environments are compared, with particular consideration being given to the difficulties associated with the characterization of the respective transport parameters. Results are presented which show that the diffusion of non-reactive solutes and solutes that react according to a constant partitioning ratio (K/sub d/) are highly predictable under laboratory conditions and that the diffusion coefficients for the reactive solutes can be determined with a reasonable degree of accuracy from independent measurements of bulk density, porosity, distribution coefficient and tortuosity. Field evidence is presented which shows that the distribution of environmental isotopes and chloride in thick clayey deposits is consistent with a diffusion-type transport process in these media. These results are particularly important in that they not only demonstrate the occurrence of diffusion-controlled hydrogeologic regimes, but they also demonstrate the predictability of the migration characteristics over very long time periods

  12. Hypoxic Prostate/Muscle PO2 Ratio Predicts for Outcome in Patients With Localized Prostate Cancer: Long-Term Results

    International Nuclear Information System (INIS)

    Turaka, Aruna; Buyyounouski, Mark K.; Hanlon, Alexandra L.; Horwitz, Eric M.; Greenberg, Richard E.; Movsas, Benjamin

    2012-01-01

    Purpose: To correlate tumor oxygenation status with long-term biochemical outcome after prostate brachytherapy. Methods and Materials: Custom-made Eppendorf PO 2 microelectrodes were used to obtain PO 2 measurements from the prostate (P), focused on positive biopsy locations, and normal muscle tissue (M), as a control. A total of 11,516 measurements were obtained in 57 men with localized prostate cancer immediately before prostate brachytherapy was given. The Eppendorf histograms provided the median PO 2 , mean PO 2 , and % 2 ratio on BF. Results: With a median follow-up time of 8 years, 12 men had ASTRO BF and 8 had Phoenix BF. On multivariate analysis, P/M PO 2 ratio 2 ratio 2 ratio) significantly predicts for poor long-term biochemical outcome, suggesting that novel hypoxic strategies should be investigated.

  13. Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery

    Science.gov (United States)

    Englot, Dario J.; Nagarajan, Srikantan S.; Imber, Brandon S.; Raygor, Kunal P.; Honma, Susanne M.; Mizuiri, Danielle; Mantle, Mary; Knowlton, Robert C.; Kirsch, Heidi E.; Chang, Edward F.

    2015-01-01

    Objective The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables non-invasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the pre-surgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. Methods We performed a retrospective cohort study of focal epilepsy patients who received MEG for interictal spike mapping followed by surgical resection at our institution. Results We studied 132 surgical patients, with mean post-operative follow-up of 3.6 years (minimum 1 year). Dipole source modelling was successful in 103 (78%) patients, while no interictal spikes were seen in others. Among patients with successful dipole modelling, MEG findings were concordant with and specific to: i) the region of resection in 66% of patients, ii) invasive electrocorticography (ECoG) findings in 67% of individuals, and iii) the MRI abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure-freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were non-specific or discordant with the region of resection (χ2 = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp EEG, and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (2.23–11.8, 95% CI). Significance MEG is a valuable tool for non-invasive interictal spike mapping in epilepsy surgery, including patients with non-localized findings on long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated

  14. Time scaling internal state predictive control of a solar plant

    Energy Technology Data Exchange (ETDEWEB)

    Silva, R.N. [DEE-FCT/UNL, Caparica (Portugal); Rato, L.M. [INESC-ID/University, Evora (Portugal); Lemos, J.M. [INESC-ID/IST, Lisboa (Portugal)

    2003-12-01

    The control of a distributed collector solar field is addressed in this work, exploiting the plant's transport characteristic. The plant is modeled by a hyperbolic type partial differential equation (PDE) where the transport speed is the manipulated flow, i.e. the controller output. The model has an external distributed source, which is the solar radiation captured along the collector, approximated to depend only of time. From the solution of the PDE, a linear discrete state space model is obtained by using time-scaling and the redefinition of the control input. This method allows overcoming the dependency of the time constants with the operating point. A model-based predictive adaptive controller is derived with the internal temperature distribution estimated with a state observer. Experimental results at the solar power plant are presented, illustrating the advantages of the approach under consideration. (author)

  15. Data-Driven Predictive Direct Load Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Knudsen, Torben; Wisniewski, Rafal

    2015-01-01

    A predictive control using subspace identification is applied for the smart grid integration of refrigeration systems under a direct load control scheme. A realistic demand response scenario based on regulation of the electrical power consumption is considered. A receding horizon optimal control...... is proposed to fulfil two important objectives: to secure high coefficient of performance and to participate in power consumption management. Moreover, a new method for design of input signals for system identification is put forward. The control method is fully data driven without an explicit use of model...... against real data. The performance improvement results in a 22% reduction in the energy consumption. A comparative simulation is accomplished showing the superiority of the method over the existing approaches in terms of the load following performance....

  16. Predictive Smart Grid Control with Exact Aggregated Power Constraints

    DEFF Research Database (Denmark)

    Trangbæk, K; Petersen, Mette Højgaard; Bendtsen, Jan Dimon

    2012-01-01

    of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The load variations on the grid arise on one hand from varying......This chapter deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high-level MPC controller, a second level of so-called aggregators,which reduces the computational and communication related load on the high-level control, and a lower level...... consumption, and on the other hand from natural variations in power production from e.g. wind turbines. The consumers represent energy-consuming units such as heat pumps, car batteries etc. These units obviously have limits on how much power and energy they can consume at any given time, which impose...

  17. Model predictive control approach for a CPAP-device

    Directory of Open Access Journals (Sweden)

    Scheel Mathias

    2017-09-01

    Full Text Available The obstructive sleep apnoea syndrome (OSAS is characterized by a collapse of the upper respiratory tract, resulting in a reduction of the blood oxygen- and an increase of the carbon dioxide (CO2 - concentration, which causes repeated sleep disruptions. The gold standard to treat the OSAS is the continuous positive airway pressure (CPAP therapy. The continuous pressure keeps the upper airway open and prevents the collapse of the upper respiratory tract and the pharynx. Most of the available CPAP-devices cannot maintain the pressure reference [1]. In this work a model predictive control approach is provided. This control approach has the possibility to include the patient’s breathing effort into the calculation of the control variable. Therefore a patient-individualized control strategy can be developed.

  18. Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems

    DEFF Research Database (Denmark)

    Morstyn, Thomas; Hredzak, Branislav; Aguilera, Ricardo P.

    2018-01-01

    , and converter current constraints to be addressed. In addition, nonlinear variations in the charge and discharge efficiencies of lithium ion batteries are analyzed and included in the control strategy. Real-time digital simulations were carried out for an islanded microgrid based on the IEEE 13 bus prototypical......This brief proposes a new convex model predictive control (MPC) strategy for dynamic optimal power flow between battery energy storage (ES) systems distributed in an ac microgrid. The proposed control strategy uses a new problem formulation, based on a linear $d$ – $q$ reference frame voltage...... feeder, with distributed battery ES systems and intermittent photovoltaic generation. It is shown that the proposed control strategy approaches the performance of a strategy based on nonconvex optimization, while reducing the required computation time by a factor of 1000, making it suitable for a real...

  19. Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

    Directory of Open Access Journals (Sweden)

    M. Sridevi

    2010-10-01

    Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

  20. Dynamics and control of quadcopter using linear model predictive control approach

    Science.gov (United States)

    Islam, M.; Okasha, M.; Idres, M. M.

    2017-12-01

    This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

  1. Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems

    International Nuclear Information System (INIS)

    Cai, K.; Wonham, W. M.

    2009-01-01

    A purely distributed control paradigm is proposed for discrete-event systems (DES). In contrast to control by one or more external supervisors, distributed control aims to design built-in strategies for individual agents. First a distributed optimal nonblocking control problem is formulated. To solve it, a top-down localization procedure is developed which systematically decomposes an external supervisor into local controllers while preserving optimality and nonblockingness. An efficient localization algorithm is provided to carry out the computation, and an automated guided vehicles (AGV) example presented for illustration. Finally, the 'easiest' and 'hardest' boundary cases of localization are discussed.

  2. Malignant melanoma and radiotherapy: past myths, excellent local control in 146 studied lesions at Georgetown University, and improving future management

    International Nuclear Information System (INIS)

    Jahanshahi, Pooya; Nasr, Nadim; Unger, Keith; Batouli, Ali; Gagnon, Gregory J.

    2012-01-01

    Introduction: Once thought to be radioresistant, emerging cellular and clinical evidence now suggests melanoma can respond to large radiation doses per fraction. Materials and Methods: We conducted a retrospective study of all patients treated with stereotactic radiosurgery and stereotactic body radiotherapy at Georgetown University Hospital from May 2002 through November 2008 and studied the classic extrapolated total dose corrected for volume (ETD vol ) model for predicting melanoma tumor response. Region-specific tumor outcomes were categorized by RECIST criteria and local control curves were estimated and analyzed when stratified by ETD vol thresholds by use of the Kaplan–Meier method. Results: Follow-up information was available for 78 lesions (49 intracranial, 8 spinal, and 21 body) with mean follow-up period of 9.2 (range, 2–36) months. 1-year local control rates for intracranial, spinal, and body tumors were 84, 100, and 72%, respectively. Treatments in general were well-tolerated. Increased ETD vol (p < 0.001) among intracranial sites resulted from larger (p < 0.001) doses per fraction combined with smaller (p < 0.001) tumor diameters. Intracranial 6-, 12-, and 24-month local control rates when treated above ETD vol threshold of 230 Gy were all 90 vs. 89, 80, and 53% below this threshold. Body 6- and 12-month local control rates when treated above ETD vol threshold of 100 Gy were 100 and 80% vs. 74 and 59% below this threshold. Discussion: By tailoring to melanoma’s unique radiobiology with large radiation doses per fraction, favorable local control was safely achieved. The ETD vol model combines the important factor of dose per fraction in melanoma treatment with a volume correction factor to predict tumor response. Although limited sample size may have prevented reaching statistical significance for local control improvements using ETD vol thresholds, optimal thresholds may exist to improve future tumor responses and further research is required.

  3. Geothermal modelling and geoneutrino flux prediction at JUNO with local heat production data

    Science.gov (United States)

    Xi, Y.; Wipperfurth, S. A.; McDonough, W. F.; Sramek, O.; Roskovec, B.; He, J.

    2017-12-01

    Geoneutrinos are mostly electron antineutrinos created from natural radioactive decays in the Earth's interior. Measurement of a geoneutrino flux at near surface detector can lead to a better understanding of the composition of the Earth, inform about chemical layering in the mantle, define the power driving mantle convection and plate tectonics, and reveal the energy supplying the geodynamo. JUNO (Jiangmen Underground Neutrino Observatory) is a 20 kton liquid scintillator detector currently under construction with an expected start date in 2020. Due to its enormous mass, JUNO will detect about 400 geoneutrinos per year, making it an ideal tool to study the Earth. JUNO is located on the passive continental margin of South China, where there is an extensive continental shelf. The continental crust surrounding the JUNO detector is between 26 and 32 km thick and represents the transition between the southern Eurasian continental plate and oceanic plate of the South China Sea.We seek to predict the geoneutrino flux at JUNO prior to data taking and announcement of the particle physics measurement. To do so requires a detail survey of the local lithosphere, as it contributes about 50% of the signal. Previous estimates of the geoneutrino signal at JUNO utilized global crustal models, with no local constraints. Regionally, the area is characterized by extensive lateral and vertical variations in lithology and dominated by Mesozoic granite intrusions, with an average heat production of 6.29 μW/m3. Consequently, at 3 times greater heat production than the globally average upper crust, these granites will generate a higher than average geoneutrino flux at JUNO. To better define the U and Th concentrations in the upper crust, we collected some 300 samples within 50 km of JUNO. By combining chemical data obtained from these samples with data for crustal structures defined by local geophysical studies, we will construct a detailed 3D geothermal model of the region. Our

  4. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    Science.gov (United States)

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  5. Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

    Science.gov (United States)

    Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

    2004-09-01

    Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

  6. Control room, emergency control system and local control panels in nuclear power plants

    International Nuclear Information System (INIS)

    1988-01-01

    The requirements on planning and construction of control boards including ergonomic-technical designing are specified in this rule. The specifications put the requirements on the design of place, process and environment of work, which are mentioned in the sections 90 and 91 of the labor-management relations act, into more concrete terms for the safety-relevant control panels as work places in a nuclear power station. The work places at control panels are not considered as video workstations in the sense of the 'Safety Rules for Video Workstations in the Office Sector' published by the General Association of the Industrial Trade Associations. The requirements are based on the operation and information technology realized at present in control panels of stationary nuclear power plants. (orig./HP) [de

  7. Predictive Local Composition Models for Solid/Liquid Equilibrium in n-Alkane Systems: Wilson Equation for Multicomponent Systems

    DEFF Research Database (Denmark)

    Coutinho, João A.P.; Stenby, Erling Halfdan

    1996-01-01

    The predictive local composition model is applied to multicomponent hydrocarbon systems with long-chain n-alkanes as solutes. The results show that it can successfully be extended to highorder systems and accurately predict the solid appearance temperature, also known as cloud point, in solutions...

  8. Optimal control in a micro gas grid of prosumers using Model Predictive Control

    NARCIS (Netherlands)

    Alkano, Desti; Nefkens, W.J.; Scherpen, Jacqueline M.A.; Volkerts, M.

    This paper studies the optimal control of a micro grid of biogas prosumers equipped with local storage devices. Excess biogas can be upgraded and injected into the low- pressure gas grid or, alternatively, shipped per lorry to be used elsewhere in an effort to create revenue. The aim of the control

  9. Effect of local automatic control rods on three-dimensional calculations of the power distribution in an RBMK

    International Nuclear Information System (INIS)

    Pogosbekyan, L.R.; Lysov, D.A.; Bronitskii, L.L.

    1993-01-01

    Numerical simulators and information systems that support nuclear reactor operators must have fast models to estimate how fuel reloads and control rod displacement affect neutron and power distributions in the core. The consequences of reloads and control rod displacement cannot be evaluated correctly without considering local automatic control-rod operations in maintaining the radial power distribution. Fast three-dimensional models to estimate the effects of reloads and displacement of the control and safety rods have already been examined. I.V. Zonov et al. used the following assumptions in their calculational model: (1) the full-scale problem could be reduced a three-dimensional fragment of a locally perturbed core, and (2) the boundary conditions of the fragment and its total power were constant. The last assumption considers approximately how local automatic control rods stabilize the radial power distribution, but three dimensional calculations with these rods are not considered. These assumptions were introduced to obtain high computational speed. I.L. Bronitskii et al. considered in more detail how moving the local automatic control rods affect the power dimensional in the three-dimensional fragment, because, with on-line monitoring of the reload process, information on control rod positions is periodically renewed, and the calculations are done in real time. This model to predict the three-dimensional power distribution to (1) do a preliminary reload analysis, and (2) prepare the core for reloading did not consider the effect of perturbations from the local automatic control rods. Here we examine a model of a stationary neutron distribution. On one hand it gives results in an acceptable computation time; on the other it is a full-scale three-dimensional model and considers how local automatic control rods affect both the radial and axial power distribution

  10. Prediction Of Formability In Sheet Metal Forming Processes Using A Local Damage Model

    International Nuclear Information System (INIS)

    Teixeira, P.; Santos, Abel; Cesar Sa, J.; Andrade Pires, F.; Barata da Rocha, A.

    2007-01-01

    The formability in sheet metal forming processes is mainly conditioned by ductile fracture resulting from geometric instabilities due to necking and strain localization. The macroscopic collapse associated with ductile failure is a result of internal degradation described throughout metallographic observations by the nucleation, growth and coalescence of voids and micro-cracks. Damage influences and is influenced by plastic deformation and therefore these two dissipative phenomena should be coupled at the constitutive level. In this contribution, Lemaitre's ductile damage model is coupled with Hill's orthotropic plasticity criterion. The coupling between damaging and material behavior is accounted for within the framework of Continuum Damage Mechanics (CDM). The resulting constitutive equations are implemented in the Abaqus/Explicit code, for the prediction of fracture onset in sheet metal forming processes. The damage evolution law takes into account the important effect of micro-crack closure, which dramatically decreases the rate of damage growth under compressive paths

  11. Maximal locality and predictive power in higher-dimensional, compactified field theories

    International Nuclear Information System (INIS)

    Kubo, Jisuke; Nunami, Masanori

    2004-01-01

    To realize maximal locality in a trivial field theory, we maximize the ultraviolet cutoff of the theory by fine tuning the infrared values of the parameters. This optimization procedure is applied to the scalar theory in D + 1 dimensional (D ≥ 4) with one extra dimension compactified on a circle of radius R. The optimized, infrared values of the parameters are then compared with the corresponding ones of the uncompactified theory in D dimensions, which is assumed to be the low-energy effective theory. We find that these values approximately agree with each other as long as R -1 > approx sM is satisfied, where s ≅ 10, 50, 50, 100 for D = 4,5,6,7, and M is a typical scale of the D-dimensional theory. This result supports the previously made claim that the maximization of the ultraviolet cutoff in a nonrenormalizable field theory can give the theory more predictive power. (author)

  12. Explicit logic circuits predict local properties of the neocortex's physiology and anatomy.

    Directory of Open Access Journals (Sweden)

    Lane Yoder

    Full Text Available BACKGROUND: Two previous articles proposed an explicit model of how the brain processes information by its organization of synaptic connections. The family of logic circuits was shown to generate neural correlates of complex psychophysical phenomena in different sensory systems. METHODOLOGY/PRINCIPAL FINDINGS: Here it is shown that the most cost-effective architectures for these networks produce correlates of electrophysiological brain phenomena and predict major aspects of the anatomical structure and physiological organization of the neocortex. The logic circuits are markedly efficient in several respects and provide the foundation for all of the brain's combinational processing of information. CONCLUSIONS/SIGNIFICANCE: At the local level, these networks account for much of the physical structure of the neocortex as well its organization of synaptic connections. Electronic implementations of the logic circuits may be more efficient than current electronic logic arrays in generating both Boolean and fuzzy logic.

  13. The potential of continuous, local atomic clock measurements for earthquake prediction and volcanology

    Directory of Open Access Journals (Sweden)

    Bondarescu Mihai

    2015-01-01

    Full Text Available Modern optical atomic clocks along with the optical fiber technology currently being developed can measure the geoid, which is the equipotential surface that extends the mean sea level on continents, to a precision that competes with existing technology. In this proceeding, we point out that atomic clocks have the potential to not only map the sea level surface on continents, but also look at variations of the geoid as a function of time with unprecedented timing resolution. The local time series of the geoid has a plethora of applications. These include potential improvement in the predictions of earthquakes and volcanoes, and closer monitoring of ground uplift in areas where hydraulic fracturing is performed.

  14. Precise Localization and Control of Catalytic Janus Micromotors using Weak Magnetic Fields

    NARCIS (Netherlands)

    Khalil, Islam S. M.; Magdanz, Veronika; Sanchez, Samuel; Schmidt, Oliver G.; Misra, Sarthak

    2015-01-01

    We experimentally demonstrate the precise localization of spherical Pt-Silica Janus micromotors (diameter 5 mu m) under the influence of controlled magnetic fields. First, we control the motion of the Janus micromotors in two-dimensional (2D) space. The control system achieves precise localization

  15. Model Predictive Control for Connected Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Kaijiang Yu

    2015-01-01

    Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

  16. Control and monitoring of the localized corrosion of zirconium in acidic chloride solutions

    International Nuclear Information System (INIS)

    Fahey, J.; Holmes, D.; Yau, T.L.

    1995-01-01

    Zirconium in acidic chloride solutions which are contaminated with ferric or cupric cations is prone to localized corrosion. This tendency can be reduced by ensuring that the zirconium surface is clean and smooth. In this paper, the effect of surface condition on the localized corrosion of zirconium in acidic chloride solutions is predicted with potentiodynamic scans. These predictions are confirmed by weight loss tests on various combinations of surface finish and acid concentrations. A real time indication of localized corrosion is seen by monitoring the electrochemical noise produced between two similar electrodes immersed in an acidic chloride solutions. Electrochemical noise monitoring correlates well with the predictions from potentiodynamic and weight loss experiments. The electrochemical noise results show that while an elevated (more anodic) potential caused by ferric ion contamination may be a necessary condition for localized corrosion, it is not a sufficient condition: A smooth, clean zirconium surface reduces the localized corrosion of zirconium

  17. Local control of muscle-invasive bladder cancer: preoperative radiotherapy and cystectomy versus cystectomy alone

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Christopher J; Pollack, Alan; Zagars, Gunar K; Dinney, Colin P; Swanson, David A; Eschenbach, Andrew C. von

    1995-05-15

    account for the differences in local control in Stage T3b patients. For patients with Stage T3b disease, the only significant difference was by grouped age (p < 0.05, chisquare), which was not a significant factor in the univariate analyses of local control. A multivariate analysis using Cox proportional hazards models revealed pretreatment hemoglobin, blood urea nitrogen (BUN) concentration, and treatment type (PREOP vs. CYST) to be independently predictive of local control. Conclusion: We document here in a large number of patients treated at a single institution that preoperative radiotherapy had a significant impact on local control for patients with clinical Stage T3b disease. Because the CYST patients were treated using modern-day surgical techniques and 80% of those with Stage T3b disease received multiagent chemotherapy, it is probable that any biases, if present, would favor the CYST group. Thus, the differences between PREOP and CYST described may be underestimated. Preoperative radiotherapy should be considered as an adjunct to chemotherapy and surgery for clinical Stage T3b patients.

  18. Field calibration and modification of scs design equation for predicting length of border under local conditions

    International Nuclear Information System (INIS)

    Choudhary, M.R.; Mustafa, U.S.

    2009-01-01

    Field tests were conducted to calibrate the existing SCS design equation in determining field border length using field data of different field lengths during 2nd and 3rd irrigations under local conditions. A single ring infiltrometer was used to estimate the water movement into and through the irrigated soil profile and in estimating the coefficients of Kostiakov infiltration function. Measurements of the unit discharge and time of advance were carried out during different irrigations on wheat irrigated fields having clay loam soil. The collected field data were used to calibrate the existing SCS design equation developed by USDA for testing its validity under local field conditions. SCS equation was modified further to improve its applicability. Results from the study revealed that the Kostiakov model over predicted the coefficients, which in turn overestimated the water advance length for boarder in the selected field using existing SCS design equation. However, the calibrated SCS design equation after parametric modification produced more satisfactory results encouraging the scientists to make its use at larger scale. (author)

  19. Assessing the variability of outcome for patients treated with localized prostate irradiation using different definitions of biochemical control

    International Nuclear Information System (INIS)

    Horwitz, Eric; Ziaja, Ellen; Vicini, Frank; Dmuchowski, Carl; Gonzalez, Jose; Stromberg, Jannifer; Brabbins, Donald; Hollander, Jay; Chen, Peter; Martinez, Alvaro

    1995-01-01

    control. All local recurrences were biopsy proven. Depending upon the definition used, substantial differences in the rates of biochemical control were observed. The differences in rates of biochemical control between all 4 groups ranged from 5 to 53% (P < .001). The Mantel Haenszel log rank test was used to evaluate the significance of pretx PSA for predicting biochemical control. Conclusion: When different definitions of biochemical control are used in assessing treatment outcome, significantly different rates of biochemical control are noted. Until a standardized definition of biochemical control is adopted, differences in treatment outcome cannot be accurately compared

  20. Malaria control. generating evidence from local to global level

    OpenAIRE

    Plüss, Bianca

    2009-01-01

    In addition of the provision of effective treatment to each case, malaria control is heavily relying on vector control with either insecticide treated mosquito nets (ITNs) or indoor residual spraying (IRS). The effectiveness of ITNs in controlling malaria in many different settings has already been comprehensively documented. On the other hand, while IRS has a long and distinguished history in malaria control, its health effects have never been properly quantified. The present thesis aimed...

  1. Local and global control of ecological and biological networks

    OpenAIRE

    Alessandro Ferrarini

    2014-01-01

    Recently, I introduced a methodological framework so that ecological and biological networks can be controlled both from inside and outside by coupling network dynamics and evolutionary modelling. The endogenous control requires the network to be optimized at the beginning of its dynamics (by acting upon nodes, edges or both) so that it will then go inertially to the desired state. Instead, the exogenous control requires that exogenous controllers act upon the network at each time step. By th...

  2. A Traffic Prediction Algorithm for Street Lighting Control Efficiency

    Directory of Open Access Journals (Sweden)

    POPA Valentin

    2013-01-01

    Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.

  3. Adjuvant Radiation Therapy Improves Local Control After Surgical Resection in Patients With Localized Adrenocortical Carcinoma

    International Nuclear Information System (INIS)

    Sabolch, Aaron; Else, Tobias; Griffith, Kent A.; Ben-Josef, Edgar; Williams, Andrew; Miller, Barbra S.; Worden, Francis; Hammer, Gary D.; Jolly, Shruti

    2015-01-01

    Purpose: Adrenocortical carcinoma (ACC) is a rare malignancy known for high rates of local recurrence, though the benefit of postoperative radiation therapy (RT) has not been established. In this study of grossly resected ACC, we compare local control of patients treated with surgery followed by adjuvant RT to a matched cohort treated with surgery alone. Methods and Materials: We retrospectively identified patients with localized disease who underwent R0 or R1 resection followed by adjuvant RT. Only patients treated with RT at our institution were included. Matching to surgical controls was on the basis of stage, surgical margin status, tumor grade, and adjuvant mitotane. Results: From 1991 to 2011, 360 ACC patients were evaluated for ACC at the University of Michigan (Ann Arbor, MI). Twenty patients with localized disease received postoperative adjuvant RT. These were matched to 20 controls. There were no statistically significant differences between the groups with regard to stage, margins, grade, or mitotane. Median RT dose was 55 Gy (range, 45-60 Gy). Median follow-up was 34 months. Local recurrence occurred in 1 patient treated with RT, compared with 12 patients not treated with RT (P=.0005; hazard ratio [HR] 12.59; 95% confidence interval [CI] 1.62-97.88). However, recurrence-free survival was no different between the groups (P=.17; HR 1.52; 95% CI 0.67-3.45). Overall survival was also not significantly different (P=.13; HR 1.97; 95% CI 0.57-6.77), with 4 deaths in the RT group compared with 9 in the control group. Conclusions: Postoperative RT significantly improved local control compared with the use of surgery alone in this case-matched cohort analysis of grossly resected ACC patients. Although this retrospective series represents the largest study to date on adjuvant RT for ACC, its findings need to be prospectively confirmed

  4. Adjuvant Radiation Therapy Improves Local Control After Surgical Resection in Patients With Localized Adrenocortical Carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Sabolch, Aaron [Department of Radiation Oncology, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Else, Tobias [Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Griffith, Kent A. [Center for Cancer Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Mchigan (United States); Ben-Josef, Edgar [Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (United States); Williams, Andrew [University of Michigan Medical School, Ann Arbor, Mchigan (United States); Miller, Barbra S. [Division of Endocrine Surgery, Department of General Surgery, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Worden, Francis [Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Hammer, Gary D. [Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Jolly, Shruti, E-mail: shrutij@med.umich.edu [Department of Radiation Oncology, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States)

    2015-06-01

    Purpose: Adrenocortical carcinoma (ACC) is a rare malignancy known for high rates of local recurrence, though the benefit of postoperative radiation therapy (RT) has not been established. In this study of grossly resected ACC, we compare local control of patients treated with surgery followed by adjuvant RT to a matched cohort treated with surgery alone. Methods and Materials: We retrospectively identified patients with localized disease who underwent R0 or R1 resection followed by adjuvant RT. Only patients treated with RT at our institution were included. Matching to surgical controls was on the basis of stage, surgical margin status, tumor grade, and adjuvant mitotane. Results: From 1991 to 2011, 360 ACC patients were evaluated for ACC at the University of Michigan (Ann Arbor, MI). Twenty patients with localized disease received postoperative adjuvant RT. These were matched to 20 controls. There were no statistically significant differences between the groups with regard to stage, margins, grade, or mitotane. Median RT dose was 55 Gy (range, 45-60 Gy). Median follow-up was 34 months. Local recurrence occurred in 1 patient treated with RT, compared with 12 patients not treated with RT (P=.0005; hazard ratio [HR] 12.59; 95% confidence interval [CI] 1.62-97.88). However, recurrence-free survival was no different between the groups (P=.17; HR 1.52; 95% CI 0.67-3.45). Overall survival was also not significantly different (P=.13; HR 1.97; 95% CI 0.57-6.77), with 4 deaths in the RT group compared with 9 in the control group. Conclusions: Postoperative RT significantly improved local control compared with the use of surgery alone in this case-matched cohort analysis of grossly resected ACC patients. Although this retrospective series represents the largest study to date on adjuvant RT for ACC, its findings need to be prospectively confirmed.

  5. Model predictive control of wind energy conversion systems

    CERN Document Server

    Yaramasu, Venkata Narasimha R

    2017-01-01

    The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.

  6. Modeling Smart Energy Systems for Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2012-01-01

    as it is produced requires a very exible and controllable power consumption. Examples of controllable electric loads are heat pumps in buildings and Electric Vehicles (EVs) that are expected to play a large role in the future danish energy system. These units in a smart energy system can potentially oer exibility...... on a time scale ranging from seconds to several days by moving power consumption, exploiting thermal inertia or battery storage capacity, respectively. Using advanced control algorithms these systems are able to reduce their own electricity costs by planning ahead and moving consumption to periods...... future price should also be available in order for the individual units to plan ahead in the most feasible way. This is necessary since Economic MPCs do not respond to the absolute cost of electricity, but to variations of the price over the prediction horizon. Economic MPC is ideal for price responsive...

  7. Structural Acoustic Prediction and Interior Noise Control Technology

    Science.gov (United States)

    Mathur, G. P.; Chin, C. L.; Simpson, M. A.; Lee, J. T.; Palumbo, Daniel L. (Technical Monitor)

    2001-01-01

    This report documents the results of Task 14, "Structural Acoustic Prediction and Interior Noise Control Technology". The task was to evaluate the performance of tuned foam elements (termed Smart Foam) both analytically and experimentally. Results taken from a three-dimensional finite element model of an active, tuned foam element are presented. Measurements of sound absorption and sound transmission loss were taken using the model. These results agree well with published data. Experimental performance data were taken in Boeing's Interior Noise Test Facility where 12 smart foam elements were applied to a 757 sidewall. Several configurations were tested. Noise reductions of 5-10 dB were achieved over the 200-800 Hz bandwidth of the controller. Accelerometers mounted on the panel provided a good reference for the controller. Configurations with far-field error microphones outperformed near-field cases.

  8. System Identification, Prediction, Simulation and Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    a Gauss-Newton search direction is applied. 3) Amongst numerous model types, often met in control applications, only the Non-linear ARMAX (NARMAX) model, representing input/output description, is examined. A simulated example confirms that a neural network has the potential to perform excellent System......The intention of this paper is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: 1) Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. 2) Amongst numerous training algorithms, only the Recursive Prediction Error Method using...

  9. Model Predictive Voltage Control of Wind Power Plants

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei

    2018-01-01

    the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...

  10. Explicit Nonlinear Model Predictive Control Theory and Applications

    CERN Document Server

    Grancharova, Alexandra

    2012-01-01

    Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Ø  Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; �...

  11. Fatigue life prediction method for contact wire using maximum local stress

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean [Sungkyunkwan University, Suwon (Korea, Republic of); Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon [Korea Railroad Research Institute, Uiwang (Korea, Republic of)

    2015-01-15

    Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

  12. Ocean Predictability and Uncertainty Forecasts Using Local Ensemble Transfer Kalman Filter (LETKF)

    Science.gov (United States)

    Wei, M.; Hogan, P. J.; Rowley, C. D.; Smedstad, O. M.; Wallcraft, A. J.; Penny, S. G.

    2017-12-01

    Ocean predictability and uncertainty are studied with an ensemble system that has been developed based on the US Navy's operational HYCOM using the Local Ensemble Transfer Kalman Filter (LETKF) technology. One of the advantages of this method is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates operational observations using ensemble method. The background covariance during this assimilation process is implicitly supplied with the ensemble avoiding the difficult task of developing tangent linear and adjoint models out of HYCOM with the complicated hybrid isopycnal vertical coordinate for 4D-VAR. The flow-dependent background covariance from the ensemble will be an indispensable part in the next generation hybrid 4D-Var/ensemble data assimilation system. The predictability and uncertainty for the ocean forecasts are studied initially for the Gulf of Mexico. The results are compared with another ensemble system using Ensemble Transfer (ET) method which has been used in the Navy's operational center. The advantages and disadvantages are discussed.

  13. Fatigue life prediction method for contact wire using maximum local stress

    International Nuclear Information System (INIS)

    Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean; Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon

    2015-01-01

    Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

  14. Study of Model Predictive Control for Path-Following Autonomous Ground Vehicle Control under Crosswind Effect

    Directory of Open Access Journals (Sweden)

    Fitri Yakub

    2016-01-01

    Full Text Available We present a comparative study of model predictive control approaches of two-wheel steering, four-wheel steering, and a combination of two-wheel steering with direct yaw moment control manoeuvres for path-following control in autonomous car vehicle dynamics systems. Single-track mode, based on a linearized vehicle and tire model, is used. Based on a given trajectory, we drove the vehicle at low and high forward speeds and on low and high road friction surfaces for a double-lane change scenario in order to follow the desired trajectory as close as possible while rejecting the effects of wind gusts. We compared the controller based on both simple and complex bicycle models without and with the roll vehicle dynamics for different types of model predictive control manoeuvres. The simulation result showed that the model predictive control gave a better performance in terms of robustness for both forward speeds and road surface variation in autonomous path-following control. It also demonstrated that model predictive control is useful to maintain vehicle stability along the desired path and has an ability to eliminate the crosswind effect.

  15. Comparison of H-infinity control and generalized predictive control for a laser scanner system

    DEFF Research Database (Denmark)

    Ordys, A.W.; Stoustrup, Jakob; Smillie, I.

    2000-01-01

    This paper describes tests performed on a laser scanner system to assess the feasibility of H-infinity control and generalized predictive control design techniques in achieving a required performance in a trajectory folowing problem. The two methods are compared with respect to achieved scan times...

  16. Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

    Directory of Open Access Journals (Sweden)

    Shaowei Sang

    Full Text Available Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF, a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose.Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8% imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags.Imported DF cases and mosquito

  17. Thailand Momentum on Policy and Practice in Local Legislation on Dengue Vector Control

    Directory of Open Access Journals (Sweden)

    Adisak Bhumiratana

    2014-01-01

    Full Text Available Over a past decade, an administrative decentralization model, adopted for local administration development in Thailand, is replacing the prior centralized (top-down command system. The change offers challenges to local governmental agencies and other public health agencies at all the ministerial, regional, and provincial levels. A public health regulatory and legislative framework for dengue vector control by local governmental agencies is a national topic of interest because dengue control program has been integrated into healthcare services at the provincial level and also has been given priority in health plans of local governmental agencies. The enabling environments of local administrations are unique, so this critical review focuses on the authority of local governmental agencies responsible for disease prevention and control and on the functioning of local legislation with respect to dengue vector control and practices.

  18. Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

    DEFF Research Database (Denmark)

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei

    2018-01-01

    This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...

  19. Local Measurement of Fuel Energy Deposition and Heat Transfer Environment During Fuel Lifetime Using Controlled Calorimetry

    International Nuclear Information System (INIS)

    Don W. Miller; Andrew Kauffmann; Eric Kreidler; Dongxu Li; Hanying Liu; Daniel Mills; Thomas D. Radcliff; Joseph Talnagi

    2001-01-01

    A comprehensive description of the accomplishments of the DOE grant titled, ''Local Measurement of Fuel Energy Deposition and Heat Transfer Environment During Fuel Lifetime using Controlled Calorimetry''

  20. Locally advanced rectal cancer: post-chemoradiotherapy ADC histogram analysis for predicting a complete response.

    Science.gov (United States)

    Cho, Seung Hyun; Kim, Gab Chul; Jang, Yun-Jin; Ryeom, Hunkyu; Kim, Hye Jung; Shin, Kyung-Min; Park, Jun Seok; Choi, Gyu-Seog; Kim, See Hyung

    2015-09-01

    The value of diffusion-weighted imaging (DWI) for reliable differentiation between pathologic complete response (pCR) and residual tumor is still unclear. Recently, a few studies reported that histogram analysis can be helpful to monitor the therapeutic response in various cancer research. To investigate whether post-chemoradiotherapy (CRT) apparent diffusion coefficient (ADC) histogram analysis can be helpful to predict a pCR in locally advanced rectal cancer (LARC). Fifty patients who underwent preoperative CRT followed by surgery were enrolled in this retrospective study, non-pCR (n = 41) and pCR (n = 9), respectively. ADC histogram analysis encompassing the whole tumor was performed on two post-CRT ADC600 and ADC1000 (b factors 0, 600 vs. 0, 1000 s/mm(2)) maps. Mean, minimum, maximum, SD, mode, 10th, 25th, 50th, 75th, 90th percentile ADCs, skewness, and kurtosis were derived. Diagnostic performance for predicting pCR was evaluated and compared. On both maps, 10th and 25th ADCs showed better diagnostic performance than that using mean ADC. Tenth percentile ADCs revealed the best diagnostic performance on both ADC600 (AZ 0.841, sensitivity 100%, specificity 70.7%) and ADC1000 (AZ 0.821, sensitivity 77.8%, specificity 87.8%) maps. In comparison between 10th percentile and mean ADC, the specificity was significantly improved on both ADC600 (70.7% vs. 53.7%; P = 0.031) and ADC1000 (87.8% vs. 73.2%; P = 0.039) maps. Post-CRT ADC histogram analysis is helpful for predicting pCR in LARC, especially, in improving the specificity, compared with mean ADC. © The Foundation Acta Radiologica 2014.

  1. Output Feedback Stabilization with Nonlinear Predictive Control: Asymptotic properties

    Directory of Open Access Journals (Sweden)

    Lars Imsland

    2003-07-01

    Full Text Available State space based nonlinear model predictive control (NM PC needs the state for the prediction of the system behaviour. Unfortunately, for most applications, not all states are directly measurable. To recover the unmeasured states, typically a stable state observer is used. However, this implies that the stability of the closed-loop should be examined carefully, since no general nonlinear separation principle exists. Recently semi-global practical stability results for output feedback NMPC using a high-gain observer for state estimation have been established. One drawback of this result is that (in general the observer gain must be increased, if the desired set the state should converge to is made smaller. We show that under slightly stronger assumptions, not only practical stability, but also convergence of the system states and observer error to the origin for a sufficiently large but bounded observer gain can be achieved.

  2. Streamlining Local Behaviour Through Communication, Incentives and Control: A Case Study of Local Environmental Policies in China

    Directory of Open Access Journals (Sweden)

    Thomas Heberer

    2011-01-01

    Full Text Available This article describes how China uses evaluation ratings and monitoring as incentives in order to foster the implementation of environmental policies at the local level. It is argued that decentralisation in China leaves room for actors at the local levels to manoeuver and bargain with those on higher levels for flexible adjustment of implementation policies according to local conditions. However, decentralisation is accompanied by significant institutional changes in the structure of intergovernmental communication, incentives and control. Accordingly, decentralisation in China exhibits a specific design which leaves space for divergent local environmental policies while also engendering “grass-roots mechanisms”. On the whole, this new institutional setting benefits the implementation of environmental policies.

  3. local

    Directory of Open Access Journals (Sweden)

    Abílio Amiguinho

    2005-01-01

    Full Text Available The process of socio-educational territorialisation in rural contexts is the topic of this text. The theme corresponds to a challenge to address it having as main axis of discussion either the problem of social exclusion or that of local development. The reasons to locate the discussion in this last field of analysis are discussed in the first part of the text. Theoretical and political reasons are there articulated because the question is about projects whose intentions and practices call for the political both in the theoretical debate and in the choices that anticipate intervention. From research conducted for several years, I use contributions that aim at discuss and enlighten how school can be a potential locus of local development. Its identification and recognition as local institution (either because of those that work and live in it or because of those that act in the surrounding context are crucial steps to progressively constitute school as a partner for development. The promotion of the local values and roots, the reconstruction of socio-personal and local identities, the production of sociabilities and the equation and solution of shared problems were the dimensions of a socio-educative intervention, markedly globalising. This scenario, as it is argued, was also, intentionally, one of transformation and of deliberate change of school and of the administration of the educative territoires.

  4. Profile control simulations and experiments on TCV : A controller test environment and results using a model-based predictive controller

    NARCIS (Netherlands)

    Maljaars, E.; Felici, F.; Blanken, T.C.; Galperti, C.; Sauter, O.; de Baar, M.R.; Carpanese, F.; Goodman, T.P.; Kim, D.; Kim, S.H.; Kong, M.G.; Mavkov, B.; Merle, A.; Moret, J.M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A.A.; Vu, N.M.T.

    2017-01-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety

  5. Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

    NARCIS (Netherlands)

    Maljaars, B.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J.; Nouailletas, R.; Scheffer, M.; Teplukhina, A.; Vu, T.

    2017-01-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety

  6. Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

    Institute of Scientific and Technical Information of China (English)

    Yi Zhang; Xiangjie Liu; Bin Qu

    2017-01-01

    Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.

  7. The design schemes of database and intelligent local controller in the SRRC control system

    International Nuclear Information System (INIS)

    Wang, C.J.; Chen, Jenny; Chen, J.S.; Jan, G.J.

    1994-01-01

    The control system of the SRRC has been utilized to facilitate commisioning since the beginning, and it provides operators an easy to use environment. Hence, we would like to discuss the design schemes and relationships between the user's interface, the database and the ILC (Intelligent Local Controller) levels. The whole control system in SRRC is a two-level design connected by Ethernet. From operator's view, the upper level is the CONSOLE level and the lower one is the ILC level. Those signals from, or to, equipment are connected to ILCs through analog/digital interfaces, GPIB buses, RS232 serial links, etc.; the ILC is an IEEE 1014 bus (VMEbus) based system running PSOS+ real-time multi-tasking kernel and PNA+ (TCP/IP protocols) communication software. The control software of CONSOLE level is developed in the VMS operating system on DEC workstations, and The Graphic User Interfaces are built on the X-Window/Motif environment. The control system has fulfilled the expectations of the facility commissioning group. It has also proved to be a simple, stable, accurate, easily maintained system. ((orig.))

  8. Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

    Czech Academy of Sciences Publication Activity Database

    Pčolka, M.; Žáčeková, E.; Robinett, R.; Čelikovský, Sergej; Šebek, M.

    2016-01-01

    Roč. 53, č. 1 (2016), s. 124-138 ISSN 0967-0661 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Model predictive control * Identification for control * Building climatecontrol Subject RIV: BC - Control Systems Theory Impact factor: 2.602, year: 2016 http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf

  9. Chemotherapy, brachytherapy and surgery of locally evolved uterine cervix carcinomas: prognosis factors of local control and global survival; Chimioradiotherapie, curietherapie et chirurgie des cancers du col uterin localement evolues: facteurs pronostiques de controle local et de survie globale

    Energy Technology Data Exchange (ETDEWEB)

    Laude, C.; Montella, A.; Montbarbon, X.; Malet, C.; Racadot, S.; Pommier, P. [Centre Leon-Berard, 69 - Lyon (France); Mathevet, P. [Hopital Femme-Mere-Enfant, Hospices Civils de Lyon, 69 - Lyon (France); Buenerd, A. [Centre de Pathologie Est, Hospices Civils de Lyon, 69 - Lyon (France)

    2009-10-15

    The protocol used allows an excellent local control of the uterine cervix carcinoma with an acceptable morbidity. To anticipate the presence of a tumor residue can be an evolution in the therapy management after external radiotherapy, particularly in optimized image-guided brachytherapy (MRI and PET)New utero vaginal applicators with parameters implantation allow to realise the dose complement at the distal parameters. These advances make consider an improvement of results in the management of locally evolved uterine cervix carcinomas. (N.C.)

  10. Scalable quantum computation via local control of only two qubits

    International Nuclear Information System (INIS)

    Burgarth, Daniel; Maruyama, Koji; Murphy, Michael; Montangero, Simone; Calarco, Tommaso; Nori, Franco; Plenio, Martin B.

    2010-01-01

    We apply quantum control techniques to a long spin chain by acting only on two qubits at one of its ends, thereby implementing universal quantum computation by a combination of quantum gates on these qubits and indirect swap operations across the chain. It is shown that the control sequences can be computed and implemented efficiently. We discuss the application of these ideas to physical systems such as superconducting qubits in which full control of long chains is challenging.

  11. Robot Formations Using Only Local Sensing and Control

    DEFF Research Database (Denmark)

    Fredslund, Jakob; Matarić, Maja J

    2001-01-01

    , behaviorbased algorithm that solves the problem for N robots each equipped with sonar, laser, camera, and a radio link for communicating with other robots. The method uses the idea of keeping a single friend at a desired angle (by panning the camera and keeping the friend centered in the image), and only......We study the problem of achieving global behavior in a group of robots using only local sensing and interaction, in the context of formations, where the goal is to have N mobile robots establish and maintain some predetermined geometric shape. We have devised a simple, general, robust, localized...... communicating heartbeat messages. We also developed a general analytical method for evaluating formations and applied it to our algorithm. We validate our algorithm both in simulation and with physical robots....

  12. Predictive control of thermal state of blast furnace

    Science.gov (United States)

    Barbasova, T. A.; Filimonova, A. A.

    2018-05-01

    The work describes the structure of the model for predictive control of the thermal state of a blast furnace. The proposed model contains the following input parameters: coke rate; theoretical combustion temperature, comprising: natural gas consumption, blasting temperature, humidity, oxygen, blast furnace cooling water; blast furnace gas utilization rate. The output parameter is the cast iron temperature. The results for determining the cast iron temperature were obtained following the identification using the Hammerstein-Wiener model. The result of solving the cast iron temperature stabilization problem was provided for the calculated values of process parameters of the target area of the respective blast furnace operation mode.

  13. Local geology controlled the feasibility of vitrifying Iron Age buildings.

    Science.gov (United States)

    Wadsworth, Fabian B; Heap, Michael J; Damby, David E; Hess, Kai-Uwe; Najorka, Jens; Vasseur, Jérémie; Fahrner, Dominik; Dingwell, Donald B

    2017-01-12

    During European prehistory, hilltop enclosures made from polydisperse particle-and-block stone walling were exposed to temperatures sufficient to partially melt the constituent stonework, leading to the preservation of glassy walls called 'vitrified forts'. During vitrification, the granular wall rocks partially melt, sinter viscously and densify, reducing inter-particle porosity. This process is strongly dependent on the solidus temperature, the particle sizes, the temperature-dependence of the viscosity of the evolving liquid phase, as well as the distribution and longevity of heat. Examination of the sintering behaviour of 45 European examples reveals that it is the raw building material that governs the vitrification efficiency. As Iron Age forts were commonly constructed from local stone, we conclude that local geology directly influenced the degree to which buildings were vitrified in the Iron Age. Additionally, we find that vitrification is accompanied by a bulk material strengthening of the aggregates of small sizes, and a partial weakening of larger blocks. We discuss these findings in the context of the debate surrounding the motive of the wall-builders. We conclude that if wall stability by bulk strengthening was the desired effect, then vitrification represents an Iron Age technology that failed to be effective in regions of refractory local geology.

  14. Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

    DEFF Research Database (Denmark)

    Errouissi, Rachid; Al-Durra, Ahmed; Muyeen, S.M.

    2017-01-01

    This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current...... is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded...... into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers...

  15. Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira [Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Research and Clinical Collaborations, Siemens Healthcare, Erlangen 91052 (Germany); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ (United Kingdom); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy)

    2010-04-15

    Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

  16. Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

    International Nuclear Information System (INIS)

    Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

    2010-01-01

    Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term α and the dose per fraction. The estimated values of α and OER from data fitting were 0.396 Gy -1 and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

  17. Predictive Function Control for Communication-Based Train Control (CBTC Systems

    Directory of Open Access Journals (Sweden)

    Bing Bu

    2013-01-01

    Full Text Available In Communication-Based Train Control (CBTC systems, random transmission delays and packet drops are inevitable in the wireless networks, which could result in unnecessary traction, brakes or even emergency brakes of trains, losses of line capacity and passenger dissatisfaction. This paper applies predictive function control technology with a mixed H2/∞ control approach to improve the control performances. The controller is in the state feedback form and satisfies the requirement of quadratic input and state constraints. A linear matrix inequality (LMI approach is developed to solve the control problem. The proposed method attenuates disturbances by incorporating H2/∞ into the control scheme. The control command from the automatic train operation (ATO is included in the reward function to optimize the train's running profile. The influence of transmission delays and packet drops is alleviated through improving the performances of the controller. Simulation results show that the method is effective to improve the performances and robustness of CBTC systems.

  18. Predictive IP controller for robust position control of linear servo system.

    Science.gov (United States)

    Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi

    2016-07-01

    Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Intensity-Modulated Radiotherapy for Oral Cavity Squamous Cell Carcinoma: Patterns of Failure and Predictors of Local Control

    International Nuclear Information System (INIS)

    Daly, Megan E.; Le, Quynh-Thu; Kozak, Margaret M.; Maxim, Peter G.; Murphy, James D.; Hsu, Annie; Loo, Billy W.; Kaplan, Michael J.; Fischbein, Nancy J.; Chang, Daniel T.

    2011-01-01

    Purpose: Few studies have evaluated the use of intensity-modulated radiotherapy (IMRT) for squamous cell carcinoma (SCC) of the oral cavity (OC). We report clinical outcomes and failure patterns for these patients. Methods and Materials: Between October 2002 and June 2009, 37 patients with newly diagnosed SCC of the OC underwent postoperative (30) or definitive (7) IMRT. Twenty-five patients (66%) received systemic therapy. The median follow-up was 38 months (range, 10-87 months). The median interval from surgery to RT was 5.9 weeks (range, 2.1-10.7 weeks). Results: Thirteen patients experienced local-regional failure at a median of 8.1 months (range, 2.4-31.9 months), and 2 additional patients experienced local recurrence between surgery and RT. Seven local failures occurred in-field (one with simultaneous nodal and distant disease) and two at the margin. Four regional failures occurred, two in-field and two out-of-field, one with synchronous metastases. Six patients experienced distant failure. The 3-year actuarial estimates of local control, local-regional control, freedom from distant metastasis, and overall survival were 67%, 53%, 81%, and 60% among postoperative patients, respectively, and 60%, 60%, 71%, and 57% among definitive patients. Four patients developed Grade ≥2 chronic toxicity. Increased surgery to RT interval predicted for decreased LRC (p = 0.04). Conclusions: Local-regional control for SCC of the OC treated with IMRT with or without surgery remains unsatisfactory. Definitive and postoperative IMRT have favorable toxicity profiles. A surgery-to-RT interval of <6 weeks improves local-regional control. The predominant failure pattern was local, suggesting that both improvements in target delineation and radiosensitization and/or dose escalation are needed.

  20. Supply Chain Control Principles in Local Food Production: A Norwegian Case Study

    Directory of Open Access Journals (Sweden)

    Heidi C. Dreyer

    2014-08-01

    Full Text Available Based on an analysis of the supply chain of four producers of local specialty foods, we explore how planning and control principles can be applied to align supply chain capabilities and market requirements. It has been shown that local food struggles with market access, and that the supply chain is one of the obstacles preventing local food producers from gaining a solid market position. We identify a number of features of the local food chain, analyse the obstacles and develop generic designs and control principles for local food producers.

  1. Local Government Planning Tool to Calculate Institutional and Engineering Control Costs for Brownfield Properties

    Science.gov (United States)

    This cost calculator is designed as a guide for municipal or local governments to assist in calculating their expected costs of implementing and conducting long-term stewardship of institutional controls and engineering controls at brownfield properties.

  2. Predicting, monitoring and controlling geomechanical effects of CO2 injection

    International Nuclear Information System (INIS)

    Streit, J.E.; Siggins, A.F.

    2005-01-01

    A key objective of geological carbon dioxide (CO 2 ) storage in porous rock is long-term subsurface containment of CO 2 . Fault stability and maximum sustainable pore-fluid pressures should be estimated in geomechanical studies in order to avoid damage to reservoir seals and fault seals of storage sites during CO 2 injection. Such analyses rely on predicting the evolution of effective stresses in rocks and faults during CO 2 injection. However, geomechanical analyses frequently do not incorporate poroelastic behaviour of reservoir rock, as relevant poroelastic properties are rarely known. The knowledge of rock poroelastic properties would allow the use of seismic methods for the accurate measurement of the effective stress evolution during CO 2 injection. This paper discussed key geomechanical effects of CO 2 injection into porous rock, and in particular, focused on the effects that the poroelasticity of reservoir rocks and pore pressure/stress coupling have on effective stresses. Relevant geophysical monitoring techniques were also suggested. The paper also outlined how these techniques could be applied to measure stress changes related to poroelastic rock behaviour during CO 2 injection and to test the predictions of sustainable changes in effective stress in CO 2 storage sites. It was concluded that a combination of predictive geomechanical techniques and application of geophysical monitoring techniques is a valid new concept for controlling and monitoring the geomechanical effects of CO 2 storage. 36 refs., 5 figs

  3. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  4. Predictive Solar-Integrated Commercial Building Load Control

    Energy Technology Data Exchange (ETDEWEB)

    Glasgow, Nathan [EdgePower Inc., Aspen, CO (United States)

    2017-01-31

    This report is the final technical report for the Department of Energy SunShot award number EE0007180 to EdgePower Inc., for the project entitled “Predictive Solar-Integrated Commercial Building Load Control.” The goal of this project was to successfully prove that the integration of solar forecasting and building load control can reduce demand charge costs for commercial building owners with solar PV. This proof of concept Tier 0 project demonstrated its value through a pilot project at a commercial building. This final report contains a summary of the work completed through he duration of the project. Clean Power Research was a sub-recipient on the award.

  5. Fast core prediction simulator for load follow control

    International Nuclear Information System (INIS)

    Yim, Man Sung; Lee, Sang Hoon; Lee, Un Chul

    1990-01-01

    An operator-assisting system for the reactor core control under power changing operating condition was developed. The system is consisted of core simulator routine and Xenon and Iodine initial condition generation routine. The initial condition generation routine, without exactly knowing the core status, is capable of providing accurate number densities and axial offset conditions of Xenon and Iodine after several hours of predictor- corrector calculations using the plant instrumentation signals of power level and power axial offset. The core simulator routine, even with the two node core model, gives equivalently accurate results as the one-dimensional model for the core behaviour simulation under power changing condition and can provide proper control strategies for load follow operation. The core simulator can also be used by the operator to develop remedial actions to restore the distorted power distribution by using its prediction capability

  6. Application of an empirical model in CFD simulations to predict the local high temperature corrosion potential in biomass fired boilers

    International Nuclear Information System (INIS)

    Gruber, Thomas; Scharler, Robert; Obernberger, Ingwald

    2015-01-01

    To gain reliable data for the development of an empirical model for the prediction of the local high temperature corrosion potential in biomass fired boilers, online corrosion probe measurements have been carried out. The measurements have been performed in a specially designed fixed bed/drop tube reactor in order to simulate a superheater boiler tube under well-controlled conditions. The investigated boiler steel 13CrMo4-5 is commonly used as steel for superheater tube bundles in biomass fired boilers. Within the test runs the flue gas temperature at the corrosion probe has been varied between 625 °C and 880 °C, while the steel temperature has been varied between 450 °C and 550 °C to simulate typical current and future live steam temperatures of biomass fired steam boilers. To investigate the dependence on the flue gas velocity, variations from 2 m·s −1 to 8 m·s −1 have been considered. The empirical model developed fits the measured data sufficiently well. Therefore, the model has been applied within a Computational Fluid Dynamics (CFD) simulation of flue gas flow and heat transfer to estimate the local corrosion potential of a wood chips fired 38 MW steam boiler. Additionally to the actual state analysis two further simulations have been carried out to investigate the influence of enhanced steam temperatures and a change of the flow direction of the final superheater tube bundle from parallel to counter-flow on the local corrosion potential. - Highlights: • Online corrosion probe measurements in a fixed bed/drop tube reactor. • Development of an empirical corrosion model. • Application of the model in a CFD simulation of flow and heat transfer. • Variation of boundary conditions and their effects on the corrosion potential

  7. Supply Chain Control Principles in Local Food Production: A Norwegian Case Study

    OpenAIRE

    Heidi C. Dreyer; Jan O. Strandhagen; Maria K. Thomassen; Anita Romsdal; Erik Gran

    2014-01-01

    Based on an analysis of the supply chain of four producers of local specialty foods, we explore how planning and control principles can be applied to align supply chain capabilities and market requirements. It has been shown that local food struggles with market access, and that the supply chain is one of the obstacles preventing local food producers from gaining a solid market position. We identify a number of features of the local food chain, analyse the obstacles and develop generic design...

  8. Subwavelength atom localization via amplitude and phase control of the absorption spectrum-II

    OpenAIRE

    Kapale, Kishore T.; Zubairy, M. Suhail

    2005-01-01

    Interaction of the internal states of an atom with spatially dependent standing-wave cavity field can impart position information of the atom passing through it leading to subwavelength atom localization. We recently demonstrated a new regime of atom localization [Sahrai {\\it et al.}, Phys. Rev. A {\\bf 72}, 013820 (2005)], namely sub-half-wavelength localization through phase control of electromagnetically induced transparency. This regime corresponds to extreme localization of atoms within a...

  9. Radiation dosimetry predicts IQ after conformal radiation therapy in pediatric patients with localized ependymoma

    International Nuclear Information System (INIS)

    Merchant, Thomas E.; Kiehna, Erin N.; Li Chenghong; Xiong Xiaoping; Mulhern, Raymond K.

    2005-01-01

    Purpose: To assess the effects of radiation dose-volume distribution on the trajectory of IQ development after conformal radiation therapy (CRT) in pediatric patients with ependymoma. Methods and Materials: The study included 88 patients (median age, 2.8 years ± 4.5 years) with localized ependymoma who received CRT (54-59.4 Gy) that used a 1-cm margin on the postoperative tumor bed. Patients were evaluated with tests that included IQ measures at baseline (before CRT) and at 6, 12, 24, 36, 48, and 60 months. Differential dose-volume histograms (DVH) were derived for total-brain, supratentorial-brain, and right and left temporal-lobe volumes. The data were partitioned into three dose intervals and integrated to create variables that represent the fractional volume that received dose over the specified intervals (e.g., V 0-20Gy , V 20-40Gy , V 40-65Gy ) and modeled with clinical variables to develop a regression equation to estimate IQ after CRT. Results: A total of 327 IQ tests were performed in 66 patients with infratentorial tumors and 20 with supratentorial tumors. The median follow-up was 29.4 months. For all patients, IQ was best estimated by age (years) at CRT; percent volume of the supratentorial brain that received doses between 0 and 20 Gy, 20 and 40 Gy, and 40 and 65 Gy; and time (months) after CRT. Age contributed significantly to the intercept (p > 0.0001), and the dose-volume coefficients were statistically significant (V 0-20Gy , p = 0.01; V 20-40Gy , p 40-65Gy , p = 0.04). A similar model was developed exclusively for patients with infratentorial tumors but not supratentorial tumors. Conclusion: Radiation dosimetry can be used to predict IQ after CRT in patients with localized ependymoma. The specificity of models may be enhanced by grouping according to tumor location

  10. FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer

    International Nuclear Information System (INIS)

    Lovinfosse, Pierre; Hustinx, Roland; Polus, Marc; Daele, Daniel van; Martinive, Philippe; Daenen, Frederic; Hatt, Mathieu; Visvikis, Dimitris; Koopmansch, Benjamin; Lambert, Frederic; Coimbra, Carla; Seidel, Laurence; Albert, Adelin; Delvenne, Philippe

    2018-01-01

    The aim of this study was to investigate the prognostic value of baseline 18 F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). Eighty-six patients with LARC underwent 18 F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT). The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrast NGTDM ) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4). Textural analysis of baseline 18 F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume

  11. FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Lovinfosse, Pierre; Hustinx, Roland [University of Liege, Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics CHU, Liege (Belgium); Polus, Marc; Daele, Daniel van [Centre Hospitalier Universitaire de Liege, Department of Gastro-enterology, Liege (Belgium); Martinive, Philippe [CHU and University of Liege, Division of Radiation Oncology, Department of Medical Physics, Liege (Belgium); Daenen, Frederic [Centre Hospitalier Regional de la Citadelle, Department of Nuclear Medicine, Liege (Belgium); Hatt, Mathieu; Visvikis, Dimitris [LaTIM, INSERM UMR 1101, Brest (France); Koopmansch, Benjamin; Lambert, Frederic [UniLab Liege, Centre Hospitalier Universitaire de Liege, Center for Human Genetic, Molecular Haemato-Oncology Unit, Liege (Belgium); Coimbra, Carla [Centre Hospitalier Universitaire de Liege, Department of Abdominal Surgery and Transplantation, Liege (Belgium); Seidel, Laurence; Albert, Adelin [Centre Hospitalier Universitaire de Liege, Department of Biostatistics and Medico-economic Information, Liege (Belgium); Delvenne, Philippe [Centre Hospitalier Universitaire de Liege, Department of Pathology, Liege (Belgium)

    2018-03-15

    The aim of this study was to investigate the prognostic value of baseline {sup 18}F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). Eighty-six patients with LARC underwent {sup 18}F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT). The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrast{sub NGTDM}) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4). Textural analysis of baseline {sup 18}F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than

  12. Progress in sub-femtosecond control of electron localization in ...

    Indian Academy of Sciences (India)

    2014-01-04

    Jan 4, 2014 ... Recent advances in controlled generation of intense, ultrashort ... of the electric field for near infrared (IR) wavelength at 800 nm is about 2.7 fs. .... Furthermore, the oscillation contrast and phase, depends on the kinetic energy.

  13. Chemotherapy, brachytherapy and surgery of locally evolved uterine cervix carcinomas: prognosis factors of local control and global survival

    International Nuclear Information System (INIS)

    Laude, C.; Montella, A.; Montbarbon, X.; Malet, C.; Racadot, S.; Pommier, P.; Mathevet, P.; Buenerd, A.

    2009-01-01

    The protocol used allows an excellent local control of the uterine cervix carcinoma with an acceptable morbidity. To anticipate the presence of a tumor residue can be an evolution in the therapy management after external radiotherapy, particularly in optimized image-guided brachytherapy (MRI and PET)New utero vaginal applicators with parameters implantation allow to realise the dose complement at the distal parameters. These advances make consider an improvement of results in the management of locally evolved uterine cervix carcinomas. (N.C.)

  14. Predictability, Force and (Anti-)Resonance in Complex Object Control.

    Science.gov (United States)

    Maurice, Pauline; Hogan, Neville; Sternad, Dagmar

    2018-04-18

    Manipulation of complex objects as in tool use is ubiquitous and has given humans an evolutionary advantage. This study examined the strategies humans choose when manipulating an object with underactuated internal dynamics, such as a cup of coffee. The object's dynamics renders the temporal evolution complex, possibly even chaotic, and difficult to predict. A cart-and-pendulum model, loosely mimicking coffee sloshing in a cup, was implemented in a virtual environment with a haptic interface. Participants rhythmically manipulated the virtual cup containing a rolling ball; they could choose the oscillation frequency, while the amplitude was prescribed. Three hypotheses were tested: 1) humans decrease interaction forces between hand and object; 2) humans increase the predictability of the object dynamics; 3) humans exploit the resonances of the coupled object-hand system. Analysis revealed that humans chose either a high-frequency strategy with anti-phase cup-and-ball movements or a low-frequency strategy with in-phase cup-and-ball movements. Counter Hypothesis 1, they did not decrease interaction force; instead, they increased the predictability of the interaction dynamics, quantified by mutual information, supporting Hypothesis 2. To address Hypothesis 3, frequency analysis of the coupled hand-object system revealed two resonance frequencies separated by an anti-resonance frequency. The low-frequency strategy exploited one resonance, while the high-frequency strategy afforded more choice, consistent with the frequency response of the coupled system; both strategies avoided the anti-resonance. Hence, humans did not prioritize interaction force, but rather strategies that rendered interactions predictable. These findings highlight that physical interactions with complex objects pose control challenges not present in unconstrained movements.

  15. Local uncontrollability for affine control systems with jumps

    Science.gov (United States)

    Treanţă, Savin

    2017-09-01

    This paper investigates affine control systems with jumps for which the ideal If(g1, …, gm) generated by the drift vector field f in the Lie algebra L(f, g1, …, gm) can be imbedded as a kernel of a linear first-order partial differential equation. It will lead us to uncontrollable affine control systems with jumps for which the corresponding reachable sets are included in explicitly described differentiable manifolds.

  16. Scalable Harmonization of Complex Networks With Local Adaptive Controllers

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Herzallah, R.

    2017-01-01

    Roč. 47, č. 3 (2017), s. 394-404 ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Fee dback * Fee dforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 2.350, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf

  17. The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

    Science.gov (United States)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Senior, Rebecca A; Bennett, Dominic J; Booth, Hollie; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; White, Hannah J; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Ancrenaz, Marc; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Báldi, András; Banks, John E; Barlow, Jos; Batáry, Péter; Bates, Adam J; Bayne, Erin M; Beja, Pedro; Berg, Åke; Berry, Nicholas J; Bicknell, Jake E; Bihn, Jochen H; Böhning-Gaese, Katrin; Boekhout, Teun; Boutin, Céline; Bouyer, Jérémy; Brearley, Francis Q; Brito, Isabel; Brunet, Jörg; Buczkowski, Grzegorz; Buscardo, Erika; Cabra-García, Jimmy; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Carrijo, Tiago F; Carvalho, Anelena L; Castro, Helena; Castro-Luna, Alejandro A; Cerda, Rolando; Cerezo, Alexis; Chauvat, Matthieu; Clarke, Frank M; Cleary, Daniel F R; Connop, Stuart P; D'Aniello, Biagio; da Silva, Pedro Giovâni; Darvill, Ben; Dauber, Jens; Dejean, Alain; Diekötter, Tim; Dominguez-Haydar, Yamileth; Dormann, Carsten F; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Elek, Zoltán; Entling, Martin H; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Ficetola, Gentile F; Filgueiras, Bruno K C; Fonte, Steven J; Fraser, Lauchlan H; Fukuda, Daisuke; Furlani, Dario; Ganzhorn, Jörg U; Garden, Jenni G; Gheler-Costa, Carla; Giordani, Paolo; Giordano, Simonetta; Gottschalk, Marco S; Goulson, Dave; Gove, Aaron D; Grogan, James; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hawes, Joseph E; Hébert, Christian; Helden, Alvin J; Henden, John-André; Hernández, Lionel; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Horgan, Finbarr G; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Jonsell, Mats; Jung, Thomas S; Kapoor, Vena; Kati, Vassiliki; Katovai, Eric; Kessler, Michael; Knop, Eva; Kolb, Annette; Kőrösi, Ádám; Lachat, Thibault; Lantschner, Victoria; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Letcher, Susan G; Littlewood, Nick A; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Marin-Spiotta, Erika; Marshall, E J P; Martínez, Eliana; Mayfield, Margaret M; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Naidoo, Robin; Nakamura, Akihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Neuschulz, Eike L; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Nöske, Nicole M; O'Dea, Niall; Oduro, William; Ofori-Boateng, Caleb; Oke, Chris O; Osgathorpe, Lynne M; Paritsis, Juan; Parra-H, Alejandro; Pelegrin, Nicolás; Peres, Carlos A; Persson, Anna S; Petanidou, Theodora; Phalan, Ben; Philips, T Keith; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Ribeiro, Danilo B; Richardson, Barbara A; Richardson, Michael J; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rosselli, Loreta; Rossiter, Stephen J; Roulston, T'ai H; Rousseau, Laurent; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Samnegård, Ulrika; Schüepp, Christof; Schweiger, Oliver; Sedlock, Jodi L; Shahabuddin, Ghazala; Sheil, Douglas; Silva, Fernando A B; Slade, Eleanor M; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Stout, Jane C; Struebig, Matthew J; Sung, Yik-Hei; Threlfall, Caragh G; Tonietto, Rebecca; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Vanbergen, Adam J; Vassilev, Kiril; Verboven, Hans A F; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Walker, Tony R; Wang, Yanping; Watling, James I; Wells, Konstans; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Woodcock, Ben A; Yu, Douglas W; Zaitsev, Andrey S; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

    2014-01-01

    Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015. PMID:25558364

  18. Horticultural activity predicts later localized limb status in a contemporary pre-industrial population.

    Science.gov (United States)

    Stieglitz, Jonathan; Trumble, Benjamin C; Kaplan, Hillard; Gurven, Michael

    2017-07-01

    Modern humans may have gracile skeletons due to low physical activity levels and mechanical loading. Tests using pre-historic skeletons are limited by the inability to assess behavior directly, while modern industrialized societies possess few socio-ecological features typical of human evolutionary history. Among Tsimane forager-horticulturalists, we test whether greater activity levels and, thus, increased loading earlier in life are associated with greater later-life bone status and diminished age-related bone loss. We used quantitative ultrasonography to assess radial and tibial status among adults aged 20+ years (mean ± SD age = 49 ± 15; 52% female). We conducted systematic behavioral observations to assess earlier-life activity patterns (mean time lag between behavioural observation and ultrasound = 12 years). For a subset of participants, physical activity was again measured later in life, via accelerometry, to determine whether earlier-life time use is associated with later-life activity levels. Anthropometric and demographic data were collected during medical exams. Structural decline with age is reduced for the tibia (female: -0.25 SDs/decade; male: 0.05 SDs/decade) versus radius (female: -0.56 SDs/decade; male: -0.20 SDs/decade), which is expected if greater loading mitigates bone loss. Time allocation to horticulture, but not hunting, positively predicts later-life radial status (β Horticulture  = 0.48, p = 0.01), whereas tibial status is not significantly predicted by subsistence or sedentary leisure participation. Patterns of activity- and age-related change in bone status indicate localized osteogenic responses to loading, and are generally consistent with the logic of bone functional adaptation. Nonmechanical factors related to subsistence lifestyle moderate the association between activity patterns and bone structure. © 2017 Wiley Periodicals, Inc.

  19. A generic statistical methodology to predict the maximum pit depth of a localized corrosion process

    International Nuclear Information System (INIS)

    Jarrah, A.; Bigerelle, M.; Guillemot, G.; Najjar, D.; Iost, A.; Nianga, J.-M.

    2011-01-01

    Highlights: → We propose a methodology to predict the maximum pit depth in a corrosion process. → Generalized Lambda Distribution and the Computer Based Bootstrap Method are combined. → GLD fit a large variety of distributions both in their central and tail regions. → Minimum thickness preventing perforation can be estimated with a safety margin. → Considering its applications, this new approach can help to size industrial pieces. - Abstract: This paper outlines a new methodology to predict accurately the maximum pit depth related to a localized corrosion process. It combines two statistical methods: the Generalized Lambda Distribution (GLD), to determine a model of distribution fitting with the experimental frequency distribution of depths, and the Computer Based Bootstrap Method (CBBM), to generate simulated distributions equivalent to the experimental one. In comparison with conventionally established statistical methods that are restricted to the use of inferred distributions constrained by specific mathematical assumptions, the major advantage of the methodology presented in this paper is that both the GLD and the CBBM enable a statistical treatment of the experimental data without making any preconceived choice neither on the unknown theoretical parent underlying distribution of pit depth which characterizes the global corrosion phenomenon nor on the unknown associated theoretical extreme value distribution which characterizes the deepest pits. Considering an experimental distribution of depths of pits produced on an aluminium sample, estimations of maximum pit depth using a GLD model are compared to similar estimations based on usual Gumbel and Generalized Extreme Value (GEV) methods proposed in the corrosion engineering literature. The GLD approach is shown having smaller bias and dispersion in the estimation of the maximum pit depth than the Gumbel approach both for its realization and mean. This leads to comparing the GLD approach to the GEV one

  20. Force Control for a Pneumatic Cylinder Using Generalized Predictive Controller Approach

    Directory of Open Access Journals (Sweden)

    Ahmad ’Athif Mohd Faudzi

    2014-01-01

    Full Text Available Pneumatic cylinder is a well-known device because of its high power to weight ratio, easy use, and environmental safety. Pneumatic cylinder uses air as its power source and converts it to a possible movement such as linear and rotary movement. In order to control the pneumatic cylinder, controller algorithm is needed to control the on-off solenoid valve with encoder and pressure sensor as the feedback inputs. In this paper, generalized predictive controller (GPC is proposed as the control strategy for the pneumatic cylinder force control. To validate and compare the performance, proportional-integral (PI controller is also presented. Both controllers algorithms GPC and PI are developed using existing linear model of the cylinder from previous research. Results are presented in simulation and experimental approach using MATLAB-Simulink as the platform. The results show that the GPC is capable of fast response with low steady state error and percentage overshoot compared to PI.

  1. Local, distributed topology control for large-scale wireless ad-hoc networks

    NARCIS (Netherlands)

    Nieberg, T.; Hurink, Johann L.

    In this document, topology control of a large-scale, wireless network by a distributed algorithm that uses only locally available information is presented. Topology control algorithms adjust the transmission power of wireless nodes to create a desired topology. The algorithm, named local power

  2. Distributed illumination control with local sensing and actuation in networked lighting systems

    NARCIS (Netherlands)

    Caicedo Fernandez, D.R.; Pandharipande, A.

    2013-01-01

    We consider the problem of illumination control in a networked lighting system wherein luminaires have local sensing and actuation capabilities. Each luminaire (i) consists of a light emitting diode (LED) based light source dimmable by a local controller, (ii) is actuated based on sensing

  3. Prediction of macroscopic and local stress-strain behaviors of perforated plates under primary and secondary creep conditions

    International Nuclear Information System (INIS)

    Igari, Toshihide; Tokiyoshi, Takumi; Mizokami, Yorikata

    2000-01-01

    Prediction methods of macroscopic and local creep behaviors of perforated plates are examined in order to apply these methods to the structural design of perforated structures such as heat exchangers used in elevated temperatures. Both primary and secondary creeps are considered for predicting macroscopic and local creep behaviors of perorated plates which are made of actual structural materials. Both uniaxial and multiaxial loading of perforated plates are taken into consideration. The concept of effective stress is applied to the prediction of macroscopic creep behaviors of perforated plates, and the predicted results are compared with the numerical results by FEM for the unit section of perorated plated under creep, in order to confirm the propriety of the proposed method. Based on the idea that stress exponents in creep equations govern the stress distribution of perforated plates, a modified Neuber's rule is used for predicting local stress and strain concentrations. The propriety of this prediction method is shown through a comparison of the prediction with the numerical results by FEM for the unit section of perforated plates under creep, and experimental results by the Moire method. (author)

  4. Clinical implication of negative conversion of predicted circumferential resection margin status after preoperative chemoradiotherapy for locally advanced rectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Nam Kwon [Department of Radiation Oncology, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of); Kim, Chul Yong, E-mail: kcyro@korea.ac.kr [Department of Radiation Oncology, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of); Park, Young Je; Yang, Dae Sik; Yoon, Won Sup [Department of Radiation Oncology, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of); Kim, Seon Hahn; Kim, Jin [Division of Colorectal Surgery, Department of Surgery, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of)

    2014-02-15

    Objective: To evaluate the prognostic implication of the negative conversion of predicted circumferential resection margin status before surgery in patients with locally advanced rectal cancer with predicted circumferential resection margin involvement. Methods: Thirty-eight patients (28 men, 10 women; median age, 61 years; age range, 39–80 years) with locally advanced rectal cancer with predicted circumferential resection margin involvement who underwent preoperative chemoradiotherapy followed by radical surgery were analyzed. Involvement of the circumferential resection margin was predicted on the basis of pre- and post-chemoradiotherapy magnetic resonance imaging. The primary endpoints were 3-year local recurrence-free survival and overall survival. Results: The median follow-up time was 41.1 months (range, 13.9–85.2 months). The negative conversion rate of predicted circumferential resection margin status after preoperative chemoradiotherapy was 65.8%. Patients who experienced negative conversion of predicted circumferential resection margin status had a significantly higher 3-year local recurrence-free survival rate (100.0% vs. 76.9%; P = 0.013), disease-free survival rate (91.7% vs. 59.3%; P = 0.023), and overall survival rate (96.0% vs. 73.8%; P = 0.016) than those who had persistent circumferential resection margin involvement. Conclusions: The negative conversion of the predicted circumferential resection margin status as predicted by magnetic resonance imaging will assist in individual risk stratification as a predictive factor for treatment response and survival before surgery. These findings may help physicians determine whether to administer more intense adjuvant chemotherapy or change the surgical plan for patients displaying resistance to preoperative chemoradiotherapy.

  5. From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

    KAUST Repository

    Cannistraci, C.V.

    2013-04-08

    Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

  6. Constrained Fuzzy Predictive Control Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Oussama Ait Sahed

    2015-01-01

    Full Text Available A fuzzy predictive controller using particle swarm optimization (PSO approach is proposed. The aim is to develop an efficient algorithm that is able to handle the relatively complex optimization problem with minimal computational time. This can be achieved using reduced population size and small number of iterations. In this algorithm, instead of using the uniform distribution as in the conventional PSO algorithm, the initial particles positions are distributed according to the normal distribution law, within the area around the best position. The radius limiting this area is adaptively changed according to the tracking error values. Moreover, the choice of the initial best position is based on prior knowledge about the search space landscape and the fact that in most practical applications the dynamic optimization problem changes are gradual. The efficiency of the proposed control algorithm is evaluated by considering the control of the model of a 4 × 4 Multi-Input Multi-Output industrial boiler. This model is characterized by being nonlinear with high interactions between its inputs and outputs, having a nonminimum phase behaviour, and containing instabilities and time delays. The obtained results are compared to those of the control algorithms based on the conventional PSO and the linear approach.

  7. Study on Noise Prediction Model and Control Schemes for Substation

    Science.gov (United States)

    Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods. PMID:24672356

  8. Prediction models and control algorithms for predictive applications of setback temperature in cooling systems

    International Nuclear Information System (INIS)

    Moon, Jin Woo; Yoon, Younju; Jeon, Young-Hoon; Kim, Sooyoung

    2017-01-01

    Highlights: • Initial ANN model was developed for predicting the time to the setback temperature. • Initial model was optimized for producing accurate output. • Optimized model proved its prediction accuracy. • ANN-based algorithms were developed and tested their performance. • ANN-based algorithms presented superior thermal comfort or energy efficiency. - Abstract: In this study, a temperature control algorithm was developed to apply a setback temperature predictively for the cooling system of a residential building during occupied periods by residents. An artificial neural network (ANN) model was developed to determine the required time for increasing the current indoor temperature to the setback temperature. This study involved three phases: development of the initial ANN-based prediction model, optimization and testing of the initial model, and development and testing of three control algorithms. The development and performance testing of the model and algorithm were conducted using TRNSYS and MATLAB. Through the development and optimization process, the final ANN model employed indoor temperature and the temperature difference between the current and target setback temperature as two input neurons. The optimal number of hidden layers, number of neurons, learning rate, and moment were determined to be 4, 9, 0.6, and 0.9, respectively. The tangent–sigmoid and pure-linear transfer function was used in the hidden and output neurons, respectively. The ANN model used 100 training data sets with sliding-window method for data management. Levenberg-Marquart training method was employed for model training. The optimized model had a prediction accuracy of 0.9097 root mean square errors when compared with the simulated results. Employing the ANN model, ANN-based algorithms maintained indoor temperatures better within target ranges. Compared to the conventional algorithm, the ANN-based algorithms reduced the duration of time, in which the indoor temperature

  9. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

  10. Local control of globally competing patterns in coupled Swift-Hohenberg equations

    Science.gov (United States)

    Becker, Maximilian; Frenzel, Thomas; Niedermayer, Thomas; Reichelt, Sina; Mielke, Alexander; Bär, Markus

    2018-04-01

    We present analytical and numerical investigations of two anti-symmetrically coupled 1D Swift-Hohenberg equations (SHEs) with cubic nonlinearities. The SHE provides a generic formulation for pattern formation at a characteristic length scale. A linear stability analysis of the homogeneous state reveals a wave instability in addition to the usual Turing instability of uncoupled SHEs. We performed weakly nonlinear analysis in the vicinity of the codimension-two point of the Turing-wave instability, resulting in a set of coupled amplitude equations for the Turing pattern as well as left- and right-traveling waves. In particular, these complex Ginzburg-Landau-type equations predict two major things: there exists a parameter regime where multiple different patterns are stable with respect to each other and that the amplitudes of different patterns interact by local mutual suppression. In consequence, different patterns can coexist in distinct spatial regions, separated by localized interfaces. We identified specific mechanisms for controlling the position of these interfaces, which distinguish what kinds of patterns the interface connects and thus allow for global pattern selection. Extensive simulations of the original SHEs confirm our results.

  11. Multi-model predictive control method for nuclear steam generator water level

    International Nuclear Information System (INIS)

    Hu Ke; Yuan Jingqi

    2008-01-01

    The dynamics of a nuclear steam generator (SG) is very different according to the power levels and changes as time goes on. Therefore, it is an intractable as well as challenging task to improve the water level control system of the SG. In this paper, a robust model predictive control (RMPC) method is developed for the level control problem. Based on a multi-model framework, a combination of a local nominal model with a polytopic uncertain linear parameter varying (LPV) model is built to approximate the system's non-linear behavior. The optimization problem solved here is based on a receding horizon scheme involving the linear matrix inequality (LMI) technique. Closed loop stability and constraints satisfaction in the entire operating range are guaranteed by the feasibility of the optimization problem. Finally, simulation results show the effectiveness and the good performance of the proposed method

  12. Importance weighting of local flux measurements to improve reactivity predictions in nuclear systems

    Energy Technology Data Exchange (ETDEWEB)

    Dulla, Sandra; Hoh, Siew Sin; Nervo, Marta; Ravetto, Piero [Politecnico di Torino, Dipt. Energia (Italy)

    2015-07-15

    The reactivity monitoring is a key aspect for the safe operation of nuclear reactors, especially for subcritical source-driven systems. Various methods are available for both, off-line and on-line reactivity determination from direct measurements carried out on the reactor. Usually the methods are based on the inverse point kinetic model applied to signals from neutron detectors and results may be severely affected by space and spectral effects. Such effects need to be compensated and correction procedures have to be applied. In this work, a new approach is proposed, by using the full information from different local measurements to generate a global signal through a proper weighting of the signals provided by single neutron detectors. A weighting techique based on the use of the adjoint flux proves to be efficient in improving the prediction capability of inverse techniques. The idea is applied to the recently developed algorithm, named MAρTA, that can be used in both off-line and online modes.

  13. Global and local threats to coral reef functioning and existence: review and predictions

    Energy Technology Data Exchange (ETDEWEB)

    Wilkinson, C.R. [Australian Institute of Marine Sciences, Townsville, Qld. (Australia)

    1999-07-01

    Factors causing global degradation of coral reefs are examined briefly as a basis for predicting the likely consequences of increases in these factors. The earlier consensus was that widespread but localized damage from natural factors such as storms, and direct anthropogenic effects such as increased sedimentation, pollution and exploitation, posed the largest immediate threat to coral reefs. Now truly global factors associated with accelerating Global Climate Change are either damaging coral reefs or have the potential to inflict greater damage in the immediate future e.g. increases in coral bleaching and mortality, and reduction in coral calcification due to changes in sea-water chemistry with increasing carbon dioxide concentrations. Rises in sea level will probably disrupt human communities and their cultures by making coral cays uninhabitable, whereas coral reefs will sustain minimal damage from the rise in sea level. The short-term (decades) prognosis is that major reductions are almost certain in the extent and biodiversity of coral reefs, and severe disruptions to cultures and economies dependent on reef resources will occur. The long-term (centuries to millennia) prognosis is more encouraging because coral reefs have remarkable resilience to severe disruption and will probably show this resilience in the future when climate changes either stabilize or reverse.

  14. Predicting transcription factor binding sites using local over-representation and comparative genomics

    Directory of Open Access Journals (Sweden)

    Touzet Hélène

    2006-08-01

    Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

  15. Immunophenotyping does not improve predictivity of the local lymph node assay in mice.

    Science.gov (United States)

    Strauss, Volker; Kolle, Susanne N; Honarvar, Naveed; Dammann, Martina; Groeters, Sibylle; Faulhammer, Frank; Landsiedel, Robert; van Ravenzwaay, Bennard

    2015-04-01

    The local lymph node assay (LLNA) is a regulatory accepted test for the identification of skin sensitizing substances by measuring radioactive thymidine incorporation into the lymph node. However, there is evidence that LLNA is overestimating the sensitization potential of certain substance classes in particular those exerting skin irritation. Some reports describe the additional use of flow cytometry-based immunophenotyping to better discriminate irritants from sensitizing irritants in LLNA. In the present study, the 22 performance standards plus 8 surfactants were assessed using the radioactive LLNA method. In addition, lymph node cells were immunophenotyped to evaluate the specificity of the lymph node response using cell surface markers such as B220 or CD19, CD3, CD4, CD8, I-A(κ) and CD69 with the aim to allow a better discrimination above all between irritants and sensitizers, but also non-irritating sensitizers and non-sensitizers. However, the markers assessed in this study do not sufficiently differentiate between irritants and irritant sensitizers and therefore did not improve the predictive capacity of the LLNA. Copyright © 2014 John Wiley & Sons, Ltd.

  16. Perfusion MRI for the prediction of treatment response after preoperative chemoradiotherapy in locally advanced rectal cancer

    International Nuclear Information System (INIS)

    Lim, Joon Seok; Baek, Song-Ee; Kim, Myeong-Jin; Suh, Jinsuk; Kim, Ki Whang; Kim, Daehong; Myoung, Sungmin; Choi, Junjeong; Shin, Sang Joon; Kim, Nam Kyu; Keum, Ki Chang

    2012-01-01

    To evaluate the utility of perfusion MRI as a potential biomarker for predicting response to chemoradiotherapy (CRT) in locally advanced rectal cancer. Thirty-nine patients with primary rectal carcinoma who were scheduled for preoperative CRT were prospectively recruited. Perfusion MRI was performed with a 3.0-T MRI system in all patients before therapy, at the end of the 2nd week of therapy, and before surgery. The K trans (volume transfer constant) and V e (extracellular extravascular space fraction) were calculated. Before CRT, the mean tumour K trans in the downstaged group was significantly higher than that in the non-downstaged group (P = 0.0178), but there was no significant difference between tumour regression grade (TRG) responders and TRG non-responders (P = 0.1392). Repeated-measures analysis of variance (ANOVA) showed significant differences for evolution of K trans values both between downstaged and non-downstaged groups (P = 0.0215) and between TRG responders and TRG non-responders (P = 0.0001). Regarding V e , no significant differences were observed both between downstaged and non-downstaged groups (P = 0.689) or between TRG responders and TRG non-responders (P = 0.887). Perfusion MRI of rectal cancer can be useful for assessing tumoural K trans changes by CRT. Tumours with high pre-CRT K trans values tended to respond favourably to CRT, particularly in terms of downstaging criteria. (orig.)

  17. CONTROL PREDICTIVO DE UN ROBOT TIPO SCARA PREDICTIVE CONTROL OF A SCARA ROBOT

    Directory of Open Access Journals (Sweden)

    Oscar Andrés Vivas Albán

    2006-08-01

    Full Text Available Este artículo presenta una aplicación eficiente de un control por modelo de referencia sobre un robot de tipo SCARA. El control estudiado es un control predictivo funcional, el que hace uso de un modelo dinámico simplificado del robot. Los ensayos simulados se realizan sobre un robot de cuatro grados de libertad, tipo SCARA. Con el fin de comparar diferentes estrategias de control, se diseña un controlador clásico tipo PID y dos controladores basados en el modelo de referencia. En este último caso el sistema se linealiza y se desacoplada por realimentación, lo que transforma el sistema a controlar en un simple par de integradores. Al sistema lineal y desacoplado resultante se le aplica el control por par calculado y el control predictivo funcional. Los tres controladores estudiados se simulan sobre el robot SCARA con valores numéricos reales. Las pruebas permiten valorar las respuestas de estos controladores en seguimiento de trayectoria, rechazo de perturbaciones y presencia de errores en el modelado con consignas complejas similares a las utilizadas en procesos de fabricación.This paper describes an efficient approach for model based control, applied on a SCARA robot. The studied control is the predictive functional control which uses a simplified dynamical model of the robot. The simulated tests are made on a SCARA type robot, with four DOF. To compare several control strategies, a classical PID control and two model based controllers are designed. In the last case, the model is first linearized and decoupled by feedback, transforming the system into a double set of integrators. Computed torque control and predictive functional control are applied to the linear and decoupled system. The three studied controllers are simulated on the SCARA robot with real numerical values. Tracking performance, disturbance rejection and model robot mismatch are enlightened, using complex machining tasks trajectories and error presence in the modelling

  18. Predicted Mobility Edges in One-Dimensional Incommensurate Optical Lattices: An Exactly Solvable Model of Anderson Localization

    International Nuclear Information System (INIS)

    Biddle, J.; Das Sarma, S.

    2010-01-01

    Localization properties of noninteracting quantum particles in one-dimensional incommensurate lattices are investigated with an exponential short-range hopping that is beyond the minimal nearest-neighbor tight-binding model. Energy dependent mobility edges are analytically predicted in this model and verified with numerical calculations. The results are then mapped to the continuum Schroedinger equation, and an approximate analytical expression for the localization phase diagram and the energy dependent mobility edges in the ground band is obtained.

  19. Antigen localization controls T cell-mediated tumor immunity.

    Science.gov (United States)

    Zeelenberg, Ingrid S; van Maren, Wendy W C; Boissonnas, Alexandre; Van Hout-Kuijer, Maaike A; Den Brok, Martijn H M G M; Wagenaars, Jori A L; van der Schaaf, Alie; Jansen, Eric J R; Amigorena, Sebastian; Théry, Clotilde; Figdor, Carl G; Adema, Gosse J

    2011-08-01

    Effective antitumor immunotherapy requires the identification of suitable target Ags. Interestingly, many of the tumor Ags used in clinical trials are present in preparations of secreted tumor vesicles (exosomes). In this study, we compared T cell responses elicited by murine MCA101 fibrosarcoma tumors expressing a model Ag at different localizations within the tumor cell in association with secreted vesicles (exosomes), as a nonsecreted cell-associated protein, or as secreted soluble protein. Remarkably, we demonstrated that only the tumor-secreting vesicle-bound Ag elicited a strong Ag-specific CD8(+) T cell response, CD4(+) T cell help, Ag-specific Abs, and a decrease in the percentage of immunosuppressive regulatory T cells in the tumor. Moreover, in a therapeutic tumor model of cryoablation, only in tumors secreting vesicle-bound Ag could Ag-specific CD8(+) T cells still be detected up to 16 d after therapy. We concluded that the localization of an Ag within the tumor codetermines whether a robust immunostimulatory response is elicited. In vivo, vesicle-bound Ag clearly skews toward a more immunogenic phenotype, whereas soluble or cell-associated Ag expression cannot prevent or even delay outgrowth and results in tumor tolerance. This may explain why particular immunotherapies based on these vesicle-bound tumor Ags are potentially successful. Therefore, we conclude that this study may have significant implications in the discovery of new tumor Ags suitable for immunotherapy and that their location should be taken into account to ensure a strong antitumor immune response.

  20. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....