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Thai Nguyen, Vietnam

This paper addresses the problem of adaptive tracking control for uncertain fully actuated dynamical systems with additive disturbance (FDSA) based on the sliding mode. We use the adaptive mechanism to adjust the uncertain parameters in sliding mode control law which can be switched to two modes depending on the sliding surface. By choosing appropriately the parameters in control law, the desired transient time can be obtained without effects of uncertain parameters and additive disturbances. The chattering phenomenon can be minimized by a chosen constant. This control method is applied to the angles tracking control of the twin rotor multi-input multi-output system (TRMS) which have nonlinear characteristics, the input torque disturbances and the coupling between the horizontal and vertical movements. The simulation and experimental results are presented that validate the proposed solution. © 2016 Chi Nguyen Van. Source

Davydov O.,University of Strathclyde | Oanh D.T.,Thai Nguyen University
Computers and Mathematics with Applications | Year: 2011

We investigate the influence of the shape parameter in the meshless Gaussian radial basis function finite difference (RBF-FD) method with irregular centres on the quality of the approximation of the Dirichlet problem for the Poisson equation with smooth solution. Numerical experiments show that the optimal shape parameter strongly depends on the problem, but insignificantly on the density of the centres. Therefore, we suggest a multilevel algorithm that effectively finds a near-optimal shape parameter, which helps to significantly reduce the error. Comparison to the finite element method and to the generalised finite differences obtained in the flat limits of the Gaussian RBF is provided. © 2011 Elsevier Ltd. All rights reserved. Source

Nguyen M.T.,Oklahoma State University | Nguyen M.T.,Thai Nguyen University | Teague K.A.,Oklahoma State University
Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2014 | Year: 2014

In this paper, we study the integration between Compressed Sensing (CS) and clustering methods in Wireless Sensor Networks (WSNs) that significantly reduce power consumption for the networks. In theory, a base station (BS) needs to collect M measurements from the network with N sensors, then applies CS to obtain precisely all N sensor readings. In clustered networks, a cluster-head (CH) collects data from non-CH sensors in its cluster, adds all received and its own data then send the combined measurement to the BS. We further analyze the clustered network with the measurement matrix created by clustering methods, and formulate the total power consumption. Finally, we suggest the optimal number of clusters for the networks consume the least power in practice. © 2014 IEEE. Source

Nguyen V.-D.,Thai Nguyen University | Woo K.-C.,University of Nottingham Malaysia Campus
Nonlinear Dynamics | Year: 2011

A variety of nonlinear dynamic responses for a new electro-vibro-impact system is presented, with indication of chaotic behavior. By mathematical modeling of the physical system, an insight is obtained to the global system dynamics. The modeling has established a good correlation with experimental data, and hence can be used as a numerical tool to optimize the system dynamics. In particular, with respect to impact forces and progression rate, may then be achieved with minimal computational cost. © 2010 Springer Science+Business Media B.V. Source

Linh N.K.,Thai Nguyen University | Muu L.D.,Institute of Mathematics VAST
RAIRO - Operations Research | Year: 2015

An important problem in distance geometry is of determining the position of an unknown point in a given convex set such that its longest distance to a set of finite number of points is shortest. In this paper we present an algorithm based on subgradient method and convex hull computation for solving this problem. A recent improvement of Quickhull algorithm for computing the convex hull of a finite set of planar points is applied to fasten up the computations in our numerical experiments. © EDP Sciences, ROADEF, SMAI, 2015. Source

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