Nagarajan Sukavanam

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The investigation of the theory of fractional calculus has been started about three decades before. Fractional order nonlinear equations are abstract formulations for many problems arising in engineering, physics and many other fields in which the integer derivative with respect to time is replaced by a derivative of fractional order. In particular, the(More)
This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive(More)
The aim of this paper is to design a robust adaptive neural network-based hybrid position/force control scheme for robot manipulators in the presence of model uncertainties and external disturbance. The feedforward neural network employed to learn a highly nonlinear function requires no preliminary learning. The control purposes are to achieve the stability(More)