Optimization of the magnetic diagnostic for plasma shape identification in tokamak machines

Plasma shape identification is a crucial problem that needs to be tackled for controlling the plasma configuration in a tokamak machine. The usual way to cope with this issue is to solve an inverse problem based on the solution of the Grad-Shafranov equilibrium equation; the inputs to this algorithm are a certain number of magnetic field and flux measurements in points located around the plasma. The number and the location of the magnetic sensors providing the measurements affect the accuracy of the identification algorithm. In this paper we deal with the problem of assessing the minimum number of magnetic sensors that are necessary for the solution of the plasma shape identification in a tokamak machine. In particular we consider the ITER inner vessel magnetic diagnostic system and show that we can partition the available measurements in two subsets, where the measurements in the first subset can be reconstructed by means of suitable linear combinations of measurements in the second subset. This allow us to evaluate the redundancy level of the ITER inner vessel diagnostic system and to outline a suitable fault management system.