The oPtImal Measurement Probes Allocation (PIMPA) tool has been recently proposed in [8] to maximize the reliability of a tokamak diagnostic system against the failure of one or more of the processing nodes. PIMPA is based on the solution of Integer Linear Programming (ILP) models, and it minimizes the effect of the failure of a data acquisition component. In this paper we focus the attention on the physical parameters needed by the axisymmetric magnetic control system of the ITER tokamak (i.e. the plasma current, position and shape control system). First we introduce the improved ILP model which is then exploited to perform the optimal allocation of the probes needed to reconstruct the desired control variables. The improved model is also used to design some of the parameters of the data acquisition hardware (for example, the number of chassis needed to guarantee a given level of reliability to the system).
Optimal allocation of the diagnostic signals for the ITER magnetic control system / DE TOMMASI, Gianmaria; Neto, A. C.; Pironti, Alfredo; Sterle, Claudio. - (2015), pp. 1296-1302. (Intervento presentato al convegno 2015 IEEE Multi-Conference on Systems and Control (MSC'15) tenutosi a Sydney, Australia nel September 2015) [10.1109/CCA.2015.7320791].
Optimal allocation of the diagnostic signals for the ITER magnetic control system
DE TOMMASI, GIANMARIA;PIRONTI, ALFREDO;STERLE, CLAUDIO
2015
Abstract
The oPtImal Measurement Probes Allocation (PIMPA) tool has been recently proposed in [8] to maximize the reliability of a tokamak diagnostic system against the failure of one or more of the processing nodes. PIMPA is based on the solution of Integer Linear Programming (ILP) models, and it minimizes the effect of the failure of a data acquisition component. In this paper we focus the attention on the physical parameters needed by the axisymmetric magnetic control system of the ITER tokamak (i.e. the plasma current, position and shape control system). First we introduce the improved ILP model which is then exploited to perform the optimal allocation of the probes needed to reconstruct the desired control variables. The improved model is also used to design some of the parameters of the data acquisition hardware (for example, the number of chassis needed to guarantee a given level of reliability to the system).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
