Indra Narayan Kar

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This paper considers neuro-adaptive control of robotic manipulators based on sliding mode technique. Since robotic manipulators are inherently nonlinear systems, neural network (NN) based controllers have been proposed as a feasible technique to achieve consistent performance, owing to the adaptive nonlinear learning capabilities of NNs. Chebyshev neural(More)
In this paper, a Hamilton–Jacobi–Bellman (HJB) equation–based optimal control algorithm for robust controller design is proposed for nonlinear systems. The HJB equation is formulated using a suitable nonquadratic term in the performance functional to tackle constraints on the control input. Utilizing the direct method of Lyapunov stability, the controller(More)
The problem of estimating unknown frequencies of a sinusoidal signal simultaneously is a classical problem in signal and system theory. Many approaches and algorithms are proposed in literature to develop estimators for a measurable sinusoidal signal having multiple sinusoids with unknown amplitudes, frequencies and phases. In this work, an asymptotically(More)