| Passivity-based fuzzy ISMC for wind energy conversion systems with PMSG R Subramaniam, YH Joo IEEE Transactions on Systems, Man, and Cybernetics: Systems 51 (4), 2212-2220, 2019 | 53 | 2019 |
| Robust dissipativity and passivity analysis for discrete-time stochastic T–S fuzzy Cohen–Grossberg Markovian jump neural networks with mixed time delays S Ramasamy, G Nagamani, Q Zhu Nonlinear Dynamics 85, 2777-2799, 2016 | 40 | 2016 |
| TS fuzzy-based sliding mode controller design for discrete-time nonlinear model and its applications R Subramaniam, D Song, YH Joo Information Sciences 519, 183-199, 2020 | 39 | 2020 |
| Robust dissipativity and passivity analysis for discrete‐time stochastic neural networks with time‐varying delay G Nagamani, S Ramasamy, P Balasubramaniam Complexity 21 (3), 47-58, 2016 | 34 | 2016 |
| Dissipativity and passivity analysis for discrete‐time complex‐valued neural networks with leakage delay and probabilistic time‐varying delays S Ramasamy, G Nagamani International Journal of Adaptive Control and Signal Processing 31 (6), 876-902, 2017 | 30 | 2017 |
| Stochastic dissipativity and passivity analysis for discrete-time neural networks with probabilistic time-varying delays in the leakage term G Nagamani, S Ramasamy Applied Mathematics and Computation 289, 237-257, 2016 | 29 | 2016 |
| Dissipativity and passivity analysis for uncertain discrete-time stochastic Markovian jump neural networks with additive time-varying delays G Nagamani, S Ramasamy Neurocomputing 174, 795-805, 2016 | 28 | 2016 |
| Dissipativity and passivity analysis for discrete-time T–S fuzzy stochastic neural networks with leakage time-varying delays based on Abel lemma approach G Nagamani, S Ramasamy Journal of the Franklin Institute 353 (14), 3313-3342, 2016 | 22 | 2016 |
| Robust extended dissipativity analysis for Markovian jump discrete-time delayed stochastic singular neural networks G Nagamani, G Soundararajan, R Subramaniam, M Azeem Neural Computing and Applications 32, 9699-9712, 2020 | 14 | 2020 |
| Further results on dissipativity analysis for Markovian jump neural networks with randomly occurring uncertainties and leakage delays T Radhika, G Nagamani, Q Zhu, S Ramasamy, R Saravanakumar Neural Computing and Applications 30, 3565-3579, 2018 | 11 | 2018 |
| Further results on dissipativity criterion for markovian jump discrete-time neural networks with two delay components via discrete wirtinger inequality approach S Ramasamy, G Nagamani, T Radhika Neural Processing Letters 45, 939-965, 2017 | 10 | 2017 |
| Robust stabilization of TS fuzzy systems via improved integral inequality C Karthik, G Nagamani, R Subramaniyam, Dafik Soft Computing, 1-12, 2022 | 9 | 2022 |
| Robust dissipativity and passivity based state estimation for discrete-time stochastic Markov jump neural networks with discrete and distributed time-varying delays G Nagamani, S Ramasamy, A Meyer-Baese Neural Computing and Applications 28, 717-735, 2017 | 9 | 2017 |
| Dissipativity and passivity analysis for discrete-time complex-valued neural networks with time-varying delay G Nagamani, S Ramasamy Cogent Mathematics 2 (1), 1048580, 2015 | 9 | 2015 |
| Memory‐based ISMC design of DFIG‐based wind turbine model via T‐S fuzzy approach R Subramaniyam, YH Joo IET Control Theory & Applications 15 (3), 348-359, 2021 | 8 | 2021 |
| Robust exponential stability analysis for stochastic systems with actuator faults using improved weighted relaxed integral inequality N Gnaneswaran, K Chinnasamy, S Ramasamy, Q Zhu IEEE Transactions on Systems, Man, and Cybernetics: Systems 51 (6), 3346-3357, 2019 | 5 | 2019 |
| State estimation for discrete-time neural networks with two additive time-varying delay components based on passivity theory S. Ramasamy, G. Nagamani, P. Gopalakrishnan International Journal of Pure and Applied Mathematics 106 (6), 131-141, 2016 | 3 | 2016 |
| H∞ Control design for discrete‐time nonlinear delayed systems R Subramaniyam, YH Joo International Journal of Robust and Nonlinear Control 33 (11), 6188-6210, 2023 | 2 | 2023 |
| Studies on dissipativity and passivity analysis for discrete time dynamic neural networks S Ramasamy Dindigul, 0 | | |
Nagamani GnaneswaranThe Gandhigram Rural Institute (Deemed to be University)Verified email at ruraluniv.ac.in
