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R. Senthilkumar
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. The links to all actual bibliographies of persons of the same or a similar name can be found below. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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Other persons with the same name
- R. Senthilkumar 0001 (aka: Senthilkumar Ramachandraarjunan) — K.L.N. College of Information Technology, Pottapalayam, India
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2020 – today
- 2023
- [j6]R. Senthilkumar, R. Balamurugan:
Adaptive Fuzzy-Based SMC for Controlling Torque Ripples in Brushless DC Motor Drive Applications. Cybern. Syst. 54(7): 1132-1153 (2023) - [j5]E. Parimalasundar, R. Senthilkumar, B. Hemanth Kumar, Kavali Janardhan, Arvind R. Singh, Mohit Bajaj, Victoriia Bereznychenko:
Artificial Neural Network-Based Experimental Investigations for Sliding Mode Control of an Induction Motor in Power Steering Applications. Int. J. Intell. Syst. 2023: 1-14 (2023) - 2022
- [j4]T. A. Anuja, M. Arun Noyal Doss, R. Senthilkumar, K. S. Rajesh, R. Brindha:
Modification of Pole Pitch and Pole Arc in Rotor Magnets for Cogging Torque Reduction in BLDC Motor. IEEE Access 10: 116709-116722 (2022)
2010 – 2019
- 2019
- [j3]R. Senthilkumar, G. M. Tamilselvan, S. Kanithan, N. Arun Vignesh:
Routing in WSNs Powered by a Hybrid Energy Storage System through a CEAR Protocol Based on Cost Welfare and Route Score Metric. Int. J. Comput. Commun. Control 14(2): 233-252 (2019) - [j2]R. Senthilkumar, G. M. Tamilselvan:
Design of a Hybrid Accumulator Architecture for Harvesting and Storing of Power in WSN using an Adaptive Power Organizing Algorithm. J. Circuits Syst. Comput. 28(8): 1950130:1-1950130:30 (2019) - 2018
- [j1]R. Senthilkumar, G. Justin Sunil Dhas:
Fractional order controller design for SEPIC converter using metaheuristic algorithm. J. Intell. Fuzzy Syst. 35(6): 6269-6276 (2018)
2000 – 2009
- 2005
- [c1]R. Senthilkumar:
Performance Improvement in the Bivariate Models by using Modified Marginal Variance of Noisy Observations for Image-Denoising Applications. WEC (5) 2005: 294-298
Coauthor Index
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