Optimised plasma stabilisation at TEXTOR with an advanced, real-time digital control scheme

Mitri, M.; Nicolai, D.; Neubauer, O.; Lambertz, H.T.; Schmidt, I.; Khilchenko, A. D.; Schweer, B.; Maier, U.; Samm, U.

doi:10.1016/j.fusengdes.2009.02.039

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…The experience gathered in building these systems indicates that the graphical development environment of LabVIEW is an interesting alternative for the addition of real time plasma diagnostics to a real time network in a multi-platform tokamak data acquisition and control environment. Time ( Time (s) 3.00 Figure 5: The divertor tile currents are sampled at 100 kHz and the divertor temperature is proportional to the outer divertor tile current. In the left diagram, the outer divertor halo current measurement (black) and ELM free current calculated in real time by the median filter selection of the 100th largest value of the previous 700 points at 1 millisecond intervals (red) are shown.…”

Section: Resultsmentioning

confidence: 99%

“…The FPGA modules control approximately 600 stepper motors with millisecond synchronization over the 27 km length of the accelerator. In fusion experiments, LabVIEW RT has also been used to calculate in real-time the plasma density profile (10 ms), the Shafranov shift (10 ms), the plasma vertical and horizontal position (20 µs) and to control the plasma shape (1 ms) in the TEXTOR tokamak [3]. Standard off-the-shelf components instead of in house designs were used to build these data acquisition and control systems.…”

Section: Introductionmentioning

confidence: 99%

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Data acquisition and real-time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

Giannone¹,

Cerna²,

Cole³

et al. 2010

Fusion Engineering and Design

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The existing VxWorks real time system for the position and shape control in ASDEX Upgrade has been extended to calculate magnetic flux surfaces in real time using a multi-core PCI Express system running LabVIEW RT 8.6. Real time signal processing of bolometers and manometers is performed with the on-board FPGA to calculate the measured radiated power flux and particle flux respectively from the raw data. Radiation feedback experiments use halo current measurements from the outer divertor with real time median filter pre-processing to remove the excursions produced by ELM's. Integration of these plasma diagnostics into the control system by the exchange of XML sheets for communicating the real time variables to be produced and consumed is in operation. Reflective memory and UDP are employed by the LabVIEW RT plasma diagnostics to communicate with the control system and other plasma diagnostics in a multi-platform real time network.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data acquisition and real-time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

Giannone¹,

Cerna²,

Cole³

et al. 2010

Fusion Engineering and Design

View full text Add to dashboard Cite

show abstract

“…The first one is used to control the plasma shape (1 ms) and to calculate the plasma vertical position (20 µs). The second system is used to calculate in real-time the plasma density profile (10 ms), and the plasma horizontal position (20 µs) [9].…”

Section: Real Time Controlmentioning

confidence: 99%

Tokamak Design as One Sustainable System

Rastovic¹

2011

NNW

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Nowadays, remote sensing technology is being used as an essential tool for monitoring and detecting oil spills to take precautions and to prevent the damages to the marine environment. As an important branch of remote sensing, satellite based synthetic aperture radar imagery (SAR) is the most effective way to accomplish these tasks. Since a marine surface with oil spill seems as a dark object because of much lower backscattered energy, the main problem is to recognize and differentiate the dark objects of oil spills from others to be formed by oceanographic and atmospheric conditions. In this study, Radarsat-1 images covering Lebanese coasts were employed for oil spill detection. For this purpose, a powerful classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) was used. As the original contribution of the paper, the network was trained by a novel heuristic optimization algorithm known as Artificial Bee Colony (ABC) method besides the conventional Backpropagation (BP) and Levenberg-Marquardt (LM) learning algorithms. A comparison and evaluation of different network training algorithms regarding reliability of detection and robustness show that for this problem best result is achieved with the Artificial Bee Colony algorithm (ABC).

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Control Systems

Dolan¹

2013

Magnetic Fusion Technology

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Optimised plasma stabilisation at TEXTOR with an advanced, real-time digital control scheme

Cited by 4 publications

References 7 publications

Data acquisition and real-time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

Data acquisition and real-time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

Tokamak Design as One Sustainable System

Control Systems

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