Optimised sensor selection for control: A Hardware-in-the-loop realization on FPGA for an EMS system

Journal of Electrical Engineering

Zolotas

et al. 2016

Self Cite

This work presents a field programmable gate array (FPGA)-based embedded software platform coupled with a softwarebased plant, forming a hardware-in-the-loop (HIL) that is used to validate a systematic sensor selection framework. The systematic sensor selection framework combines multi-objective optimization, linear-quadratic-Gaussian (LQG)-type control, and the nonlinear model of a maglev suspension. A robustness analysis of the closed-loop is followed (prior to implementation) supporting the appropriateness of the solution under parametric variation. The analysis also shows that quantization is robust under different controller gains. While the LQG controller is implemented on an FPGA, the physical process is realized in a high-level system modeling environment. FPGA technology enables rapid evaluation of the algorithms and test designs under realistic scenarios avoiding heavy time penalty associated with hardware description language (HDL) simulators. The HIL technique facilitates significant speed-up in the required execution time when compared to its software-based counterpart model. K e y w o r d s: sensor optimization, FPGA, maglev, embedded control, electromagnetic suspension, linear quadratic Gaussian, hardware-in-the-loop, FPGA-in-the-loop

“…The aforementioned matrices are given by (11)- (13) in the Appendix. The various sensor sets can be obtained by appropriate selection of the corresponding rows in the output matrix C .…”

Section: Non-linear Model Of the Emsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FPGA–Based Efficient Hardware/Software Co–Design for Industrial Systems with Consideration of Output Selection

Journal of Electrical Engineering

Zolotas

et al. 2016

Self Cite

A model-based embedded control hardware/software co-design approach for optimized sensor selection of industrial systems

2015 23rd Mediterranean Conference on Control and Automation (MED)

Tzafestas

et al. 2015

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. Moreover, the HIL technique implemented shows a significant speed-up in the required execution time when compared to the software-based model

On the issue of LQG embedded control realization in a Maglev system

2017 25th Mediterranean Conference on Control and Automation (MED)

Zolotas

2017

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