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TY - CONF AU - Hill, J.O. ED - Schaa, Volker RW ED - Costa, Isidre ED - Fernández, David ED - Matilla, Ãscar TI - Applications of Kalman State Estimation in Current Monitor Diagnostic Systems J2 - Proc. of ICALEPCS2017, Barcelona, Spain, 8-13 October 2017 C1 - Barcelona, Spain T2 - International Conference on Accelerator and Large Experimental Control Systems T3 - 16 LA - english AB - Traditionally, designers of transformer-based beam current monitor diagnostic systems are constrained by fundamental trade-offs when reducing distortion in time-domain beam-pulse facsimile waveforms while also attempting to preserve information in the frequency-domain. When modelling the sensor system with a net-work of linear time-invariant passive components, and a state-based representation based on first-order differential equations, we identify two internal dynamical states isolated from each other by the parasitic resistance in the transformer windings. They are the parasitic capacitance voltage across the transformer's windings, and the transformer inductor current. These states are typically imperfectly observed due to noise, component value variance, and sensor component network topology. We will discuss how feedback-based Kalman State Estimation implemented within digital signal-processing might be employed to reduce negative impacts of noise along with component variance, and how Kalman Estimation might also optimize the conflicting goals of beam-pulse facsimile waveform fidelity together with preservation of fre-quency domain information. PB - JACoW CP - Geneva, Switzerland SP - 1673 EP - 1677 KW - ion KW - target KW - feedback KW - simulation KW - diagnostics DA - 2018/01 PY - 2018 SN - 978-3-95450-193-9 DO - 10.18429/JACoW-ICALEPCS2017-THPHA128 UR - http://jacow.org/icalepcs2017/papers/thpha128.pdf ER -