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In this work, a Field Programmable Gate Array (FPGA)-based embedded software platform coupled with a software-based plant, forming a Hardware-In-the-Loop (HIL), is used to validate a systematic sensor selection framework. The systematic sensor selection framework combines multi-objective optimization, Linear-Quadratic-Gaussian (LQG) control, and the nonlinear model of a maglev suspension. The physical process that represents the suspension plant is realized in a high-level system modelingdoi:10.1109/med.2015.7158858 dblp:conf/med/DeliparaschosMT15 fatcat:6gzutys3pbehxnz5o2tmr6m2pe