Low-Complexity Architecture for Cyber-Physical Systems Model Identification

Vala, Charan Kumar and French, Mark and Acharyya, Amit and Al-Hashimi, Bashir M (2018) Low-Complexity Architecture for Cyber-Physical Systems Model Identification. IEEE Transactions on Circuits and Systems II: Express Briefs. ISSN 1549-7747

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We propose a low complexity architecture for cyber-physical system (CPS) model identification based on multiple-model adaptive estimation (MMAE) algorithms. The complexity reduction is achieved by reducing the number of multiplications in the filter banks of the MMAE algorithm present in the cyber component of the CPS. The architecture has been implemented using FPGA for 16, 32, 64 filter banks as part of position and velocity estimations of autonomous auto-mobile application. It has been found up to 78% reduction in multiplications is possible, which translates to the reduction of 39% LUTs, 13% FFs, 27% DSPs, and 43% power reduction when compared with the conventional architecture (without multiplications reduction) at 100MHz operating frequency. Furthermore, the proposed architecture is able to identify accurate model of auto-mobile application just within 510ns, in the presence of external disturbances and abrupt changes.

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IITH Creators:
IITH CreatorsORCiD
Acharyya, Amithttp://orcid.org/0000-0002-5636-0676
Item Type: Article
Uncontrolled Keywords: Cyber-Physical Systems , Model Identification , MMAE , MMAC , Bank of Kalman Filters , FPGA.
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 01 Mar 2019 11:13
Last Modified: 01 Mar 2019 11:13
URI: http://raiith.iith.ac.in/id/eprint/4859
Publisher URL: http://doi.org/10.1109/TCSII.2018.2881481
OA policy: http://www.sherpa.ac.uk/romeo/issn/1549-7747/
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