Zobrazeno 1 - 10
of 17
pro vyhledávání: '"M. Germin Nisha"'
Publikováno v:
Bulletin of the Polish Academy of Sciences: Technical Sciences, Vol 70, Iss 1 (2022)
Industrial processes such as batch distillation columns, supply chain, level control etc. integrate dead times in the wake of the transportation times associated with energy, mass and information. The dead time, the cause for the rise in loop variabi
Externí odkaz:
https://doaj.org/article/b214551c46ca4fb49c60d5307009512f
Autor:
P. M., Ansho, M., Germin Nisha
Publikováno v:
Journal of Electrical Engineering & Technology (19750102); May2024, Vol. 19 Issue 4, p2047-2057, 11p
Publikováno v:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 31:327-349
Process control is the interested domain of interest as the industrial high-order applications require an effective control mechanism with higher robustness. Since the conventional method of proportional integral derivative (PID) controller remains i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a3660169099c3d0cceffacfc5105854
https://doi.org/10.1142/s0218488523500174
https://doi.org/10.1142/s0218488523500174
Publikováno v:
Intelligent Automation & Soft Computing. 36:745-760
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08faa7c7b684cf94daa453ae57f7e3cb
https://doi.org/10.32604/iasc.2023.028011
https://doi.org/10.32604/iasc.2023.028011
Autor:
M. Nisha, M. Germin Nisha
Publikováno v:
Intelligent Automation & Soft Computing. 34:1399-1413
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22c0241f1f682132c72a5974eec6867a
https://doi.org/10.32604/iasc.2022.024482
https://doi.org/10.32604/iasc.2022.024482
Akademický článek
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Akademický článek
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Publikováno v:
2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC).
An effective application of Model Predictive Control by means of a multi-layer feed forward neural network as the nonlinear model of the process is discussed. The main draw back in the use of Nonlinear programming for optimization is the complexity i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64be27b5758a880f6baaf405263eea3a
https://doi.org/10.1109/icraecc43874.2019.8995025
https://doi.org/10.1109/icraecc43874.2019.8995025
Autor:
M. Germin Nisha, D. Periyasamy
Publikováno v:
2017 International Conference on Innovations in Green Energy and Healthcare Technologies (IGEHT).
Model predictive control (MPC), which works on the basis of receding horizon control has attracted the process control community due to its capability to grasp constraints on process variables, nonlinearities plus interactions among process variables
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a1825d956aeae7a49ba8eda43b2f8c4
https://doi.org/10.1109/igeht.2017.8094050
https://doi.org/10.1109/igeht.2017.8094050
Publikováno v:
International Journal of Sustainable Energy. 34:685-692
This paper proposes an advanced machine learning method, relevance vector machines (RVMs), to model photovoltaic (PV) cells with a few measured data, over a range of expected operating conditions. RVMs are established on a Bayesian formulation which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc9f4b5244149b49e4858ced86f98084
https://doi.org/10.1080/14786451.2014.885030
https://doi.org/10.1080/14786451.2014.885030