Real-time control of many plasma parameters will be an essential aspect in the development of reliable high performance operation of next step tokamaks. The main prerequisites for any feedback scheme are the precise real-time determination of the quantities to be controlled, requiring top quality and highly reliable diagnostics, and the availability of robust control algorithms.A new set of real-time diagnostics was recently implemented on JET to prove the feasibility of determining, with high accuracy and time resolution, the most important plasma quantities. Some of the signals now routinely provided in real time at JET are: (i) the internal inductance and the main confinement quantities obtained by calculating the Shafranov integrals from the pick-up coils with 2 ms time resolution; (ii) the electron temperature profile, from electron cylotron emission every 10 ms; (iii) the ion temperature and plasma toroidal velocity profiles, from charge exchange recombination spectroscopy, provided every 50 ms; and (iv) the safety factor profile, derived from the inversion of the polarimetric line integrals every 2 ms. With regard to feedback algorithms, new model-based controllers were developed to allow a more robust control of several plasma parameters.With these new tools, several real-time schemes were implemented, among which the most significant is the simultaneous control of the safety factor and the plasma pressure profiles using the additional heating systems (LH, NBI, ICRH) as actuators. The control strategy adopted in this case consists of a multi-variable model-based technique, which was implemented as a truncated singular value decomposition of an integral operator. This approach is considered essential for systems like tokamak machines, characterized by a strong mutual dependence of the various parameters and the distributed nature of the quantities, the plasma profiles, to be controlled. First encouraging results were also obtained using non-algorithmic methods like neural networks, which have been successfully applied to non-linear and ill-posed problems, for example the determination of the divertor radiated power.The real-time hardware and software architectures adopted are also described with particular attention to their relevance to ITER.

Development of real-time diagnostics and feedback algorithms for JET in view of the next step

ARENA, Paolo Pietro;
2005-01-01

Abstract

Real-time control of many plasma parameters will be an essential aspect in the development of reliable high performance operation of next step tokamaks. The main prerequisites for any feedback scheme are the precise real-time determination of the quantities to be controlled, requiring top quality and highly reliable diagnostics, and the availability of robust control algorithms.A new set of real-time diagnostics was recently implemented on JET to prove the feasibility of determining, with high accuracy and time resolution, the most important plasma quantities. Some of the signals now routinely provided in real time at JET are: (i) the internal inductance and the main confinement quantities obtained by calculating the Shafranov integrals from the pick-up coils with 2 ms time resolution; (ii) the electron temperature profile, from electron cylotron emission every 10 ms; (iii) the ion temperature and plasma toroidal velocity profiles, from charge exchange recombination spectroscopy, provided every 50 ms; and (iv) the safety factor profile, derived from the inversion of the polarimetric line integrals every 2 ms. With regard to feedback algorithms, new model-based controllers were developed to allow a more robust control of several plasma parameters.With these new tools, several real-time schemes were implemented, among which the most significant is the simultaneous control of the safety factor and the plasma pressure profiles using the additional heating systems (LH, NBI, ICRH) as actuators. The control strategy adopted in this case consists of a multi-variable model-based technique, which was implemented as a truncated singular value decomposition of an integral operator. This approach is considered essential for systems like tokamak machines, characterized by a strong mutual dependence of the various parameters and the distributed nature of the quantities, the plasma profiles, to be controlled. First encouraging results were also obtained using non-algorithmic methods like neural networks, which have been successfully applied to non-linear and ill-posed problems, for example the determination of the divertor radiated power.The real-time hardware and software architectures adopted are also described with particular attention to their relevance to ITER.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/55535
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