A model-based embedded control hardware/software co-design approach for optimized sensor selection of industrial systems
Date Issued
June 2015
DOI
10.1109/MED.2015.7158858
10.1109/MED.2015.7158858
Abstract
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 modeling environment, while the LQG controller is implemented on an FPGA. FPGAs allow to rapidly evaluate algorithms and test designs under real-world scenarios avoiding heavy time penalty associated with Hardware Description Language (HDL) simulators. In addition, the HIL technique implemented has shown a significant speed-up in the required execution time when compared to the software-based model.