FPGAs in Industrial Control Applications
ПЛИС в приложениях промышленного управления
2011-03-29
SCID: 54.1/r4fbs6pq
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Extended Kalman FilterField Programmable Gate Array (FPGA)Neural Network control systemsindustrial control applicationssensorless motor controller
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Abstract (AI)
The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs.
Key Findings
1
A dedicated FPGA-oriented design methodology was applied and discussed for developing the Extended Kalman Filter-based controller.
2
A sensorless motor controller based on the Extended Kalman Filter was developed and used to illustrate FPGA benefits for complex control applications.
3
FPGA device features and corresponding design tools are presented as enabling resources for complex control system implementation.
4
FPGA implementation of artificial intelligence-based controllers, including two short case studies of neural network control system designs, is feasible and reviewed.
5
FPGA technologies offer advantages exploitable across various research fields relevant to industrial control applications.
Research Object
Field Programmable Gate Arrays (FPGAs) used in industrial control applications
Research Subject
Their features, design tools, implementation methodologies and benefits for industrial control functions including sensorless motor control with an Extended Kalman Filter and FPGA-based neural-network/AI controllers
Publication Details
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2011-03-29
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