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|Title:||On the issue of LQG embedded control realization in a Maglev system||Authors:||Deliparaschos, Kyriakos M.
Zolotas, Argyrios C.
|Keywords:||Mathematical model;Field programmable gate arrays;Environmental management;Control systems;Energy management;Robot sensing systems;Hardware design languages||Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Field:||Engineering and Technology||Issue Date:||Jul-2017||Source:||25th Mediterranean Conference on Control and Automation, MED 2017, University of Malta, Valletta CampusValletta; Malta; 3 July 2017 through 6 July 2017||DOI:||http://dx.doi.org/10.1109/MED.2017.7984311||Conference:||Mediterranean Conference on Control and Automation||Abstract:||Sensor selection in control design receives substantial interest in the last few years. We disseminate work on Field Programmable Gate Array (FPGA)-based embedded software platform validating a systematic sensor selection framework and target efficient FPGA resource allocation. Sensor selection combines multi-objective optimization, Linear-Quadratic-Gaussian (LQG) control, applied to a Maglev suspension. The nonlinear Maglev model is realized on software platform forming a Hardware-in-the-loop (HIL) as an economic and reliable validation platform for the design setup. The LQG controller was modeled in fixed point, described in Verilog Hardware Description Language (HDL) and tied up with an ethernet core to form an FPGA-in-the-loop system prior to logic synthesis and FPGA place and route. The results illustrate efficient FPGA resource allocation level pertinent to extending to a core sensor fault tolerant scheme.||URI:||http://ktisis.cut.ac.cy/handle/10488/10292||ISBN:||978-150904533-4||DOI:||10.1109/MED.2017.7984311||Rights:||© 2017 IEEE||Type:||Conference Papers|
|Appears in Collections:||Δημοσιεύσεις σε συνέδρια/Conference papers|
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