• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.28-33
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• 2015

In this paper, we propose a near optimal controller design method for permanent magnet synchronous generators (PMSGs) of MW-class direct-driven wind turbine systems based on SDRE (State Dependent Riccati Equation) approach. Using the solution matrix of an SDRE, we parameterize the optimal controller gain. We present a simple algorithm to compute the near optimal controller gain. The proposed optimal controller can enable PMSGs to precisely track the reference speed determined by the MPPT algorithm. Finally, numerical simulation results are given to verify the effectiveness of the proposed optimal controller.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.5
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• pp.630-636
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• 1999

In this paper in optimal modulation controller for position control and anti-sway of container crane systems is designed by a recursive algorithm that determines the state weighting matrix Q of a linear quadratic performance. The optimal modulation controller is based on optimal control. The basic feature of the recursive algorithm is the reduction of the number of iterations as well as minimization of the calculations involved So in order to obtain a mathematical model which rep-resents the equation of motion of the trolley and load Lagrange equation is used. The optimal modulation controller has been verified and simulated to show that it is robust when a load dis-turbance is applied and a reference is changed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1456-1469
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• 2000

Mechanical behaviors of uniaxially fiber-reinforced metal matrix composites under transverse loading conditions were studied at room and elevated temperatures. A mono-filament composite was selecte d as a representative analysis model with perfectly bonded fiber/matrix interface assumption. The elastic-plastic and visco-plastic models were investigated by both theoretical and numerical methods. The product of triaxiality factor and effective strain as well as stress components and strain energy was obtained as a function of location to estimate the failure sites in fiber-reinforced metal matrix composite. Results showed that fiber/ matrix interfacial debond plays a key role for local failure at the room temperature, while void creation and growth in addition to the interfacial debond are major concerns at the elevated temperature. It was also shown that there would be an optimal diameter of fiber for the strong fiber-reinforced metal matrix composite.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.53-68
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• 2008

We study on the practical privacy-preserving techniques by matrix-based randomization approach. We clearly examine the relationship between the two parameters associated with the measure of privacy breach and the condition number of matrix in order to achieve the optimal transition matrix. We propose a simple formula for efficiently calculating the inverse of transition matrix which are needed in the re-construction process of random substitution algorithm, and deduce some useful connections among standard error and another parameters by obtaining condition numbers according to norms of matrix and the expectation and variance of the transformed data. Moreover we give some experimental results about our theoretical expressions by implementing random substitution algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.320-328
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• 2007

This paper presents a stiffness modeling of a low-DOF parallel robot, which takes into account of elastic deformations of joints and links, A low-DOF parallel robot is defined as a spatial parallel robot which has less than six degrees of freedom. Differently from serial chains in a full 6-DOF parallel robot, some of those in a low-DOF parallel robot may be subject to constraint forces as well as actuation forces. The reaction forces due to actuations and constraints in each serial chain can be determined by making use of the theory of reciprocal screws. It is shown that the stiffness of an F-DOF parallel robot can be modeled such that the moving platform is supported by 6 springs related to the reciprocal screws of actuations (F) and constraints (6-F). A general $6{\times}6$ stiffness matrix is derived, which is the sum of the stiffness matrices of actuations and constraints, The compliance of each spring can be precisely determined by modeling the compliance of joints and links in a serial chain as follows; a link is modeled as an Euler beam and the compliance matrix of rotational or prismatic joint is modeled as a $6{\times}6$ diagonal matrix, where one diagonal element about the rotation axis or along the sliding direction is infinite. By summing joint and link compliance matrices with respect to a reference frame and applying unit reciprocal screw to the resulting compliance matrix of a serial chain, the compliance of a spring is determined by the resulting infinitesimal displacement. In order to illustrate this methodology, the stiffness of a Tricept parallel robot has been analyzed. Finally, a numerical example of the optimal design to maximize stiffness in a specified box-shape workspace is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2298-2304
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• 2015

In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.343-352
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• 2000

In this study. the author proposes a nonhierarchical clustering method. called the "Double K-Means Clustering", which performs clustering of multivariate observations with the following algorithm: Step I: Carry out the ordinary K-means clmitering and obtain k temporary clusters with sizes $n_1$,... , $n_k$, centroids $c_$1,..., $c_k$ and pooled covariance matrix S. $\bullet$ Step II-I: Allocate the observation x, to the cluster F if it satisfies ..... where N is the total number of observations, for -i = 1, . ,N. $\bullet$ Step II-2: Update cluster sizes $n_1$,... , $n_k$, centroids $c_$1,..., $c_k$ and pooled covariance matrix S. $\bullet$ Step II-3: Repeat Steps II-I and II-2 until the change becomes negligible. The double K-means clustering is nearly "optimal" under the mixture of k multivariate normal distributions with the common covariance matrix. Also, it is nearly affine invariant, with the data-analytic implication that variable standardizations are not that required. The method is numerically demonstrated on Fisher's iris data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.661-666
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• 2010

In this paper, we apply a likelihood ratio test (LRT) to a non-negative matrix factorization (NMF) based voice activity detection (VAD) to find optimal threshold. In our approach, the NMF based VAD is expressed as Euclidean distance between noise basis vector and input basis vector which are extracted through NMF. The optimal threshold each of noise environments depend on NMF results distribution in noise region which is estimated statistical model-based VAD. According to the experimental results, the proposed approach is found to be effective for statistical model-based VAD using LRT.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.761-765
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• 2010

This paper presents the design of optimal fuzzy classifier for human detection by using genetic algorithms, one of the best-known meta-heuristic search methods. For this purpose, encoding scheme to search the optimal sequential intersection points between adjacent fuzzy membership functions is originally presented for the fuzzy classifier design for HOG (Histograms of Oriented Gradient) descriptors. The intersection points are sequentially encoded in the proposed encoding scheme to reduce the redundancy of search space occurred in the combinational problem. Furthermore, the fitness function is modified with the true-positive and true-negative of the confusion matrix instead of the total success rate. Experimental results show that the two proposed approaches give superior performance in HOG datasets.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.169-180
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• 2013

The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.