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- M. Syed Ali, R. Saravanakumar, Sabri Arik
- Neurocomputing
- 2016

- R. Saravanakumar, Kowtham Kumar, Dr . K . K . Ray
- 2009

The main objectives of this paper is aimed to control the position of a field oriented Induction Servo motor drive for a given reference input signal in a very efficient way and to compare the two control schemes using Matlab/Simulink. To design a total sliding-mode control system which is insensitive to uncertainties, including parameter variations and… (More)

- M. Syed Ali, Sabri Arik, R. Saravanakumar
- Neurocomputing
- 2015

- R. Saravanakumar, M. Syed Ali, Mingang Hua
- Soft Comput.
- 2016

- R. Saravanakumar, M. Syed Ali, Jinde Cao, He Huang
- Int. J. Systems Science
- 2016

In Wireless sensor Networks (WSNs), it is an important task to periodically collect data from an area of interest for time-sensitive applications. The Wireless sensor network (WSN) is a type of the wireless ad-hoc networks. It consisting of a large number of sensors is effective for gathering data in a variety of environments. The sensed data must be… (More)

- Grienggrai Rajchakit, R. Saravanakumar
- Neural Computing and Applications
- 2016

This draft addresses the exponential stability problem for semi-Markovian jump generalized neural networks (S-MJGNNs) with interval time-varying delays. The exponential stability conditions are derived by establishing a suitable Lyapunov–Krasovskii functional and applying new analysis method. Improved results are obtained to guarantee the exponential… (More)

- R. Saravanakumar, Muhammed Syed Ali, Choon Ki Ahn, Hamid Reza Karimi, Peng Shi
- IEEE Transactions on Neural Networks and Learning…
- 2017

This paper examines the problem of asymptotic stability for Markovian jump generalized neural networks with interval time-varying delays. Markovian jump parameters are modeled as a continuous-time and finite-state Markov chain. By constructing a suitable Lyapunov–Krasovskii functional (LKF) and using the linear matrix inequality (LMI) formulation,… (More)

- M. Syed Ali, R. Saravanakumar, Quanxin Zhu
- Neurocomputing
- 2015

- Grienggrai Rajchakit, R. Saravanakumar, Choon Ki Ahn, Hamid Reza Karimi
- Neural Networks
- 2017

This article examines the exponential stability analysis problem of generalized neural networks (GNNs) including interval time-varying delayed states. A new improved exponential stability criterion is presented by establishing a proper Lyapunov-Krasovskii functional (LKF) and employing new analysis theory. The improved reciprocally convex combination (RCC)… (More)