Vala, Charan Kumar, French, Mark, Acharyya, Amit and Al-Hashimi, Bashir (2018) Low-complexity architecture for cyber-physical systems model identification. IEEE Transactions on Circuits and Systems II: Express Briefs, 1-6. (doi:10.1109/TCSII.2018.2881481).
Abstract
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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- Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science
School of Electronics and Computer Science - Current Faculties > Faculty of Engineering and Physical Sciences
- Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Electronics & Computer Science (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg)
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