• Journal of electromagnetic engineering and science
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• v.17 no.3
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• pp.113-119
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• 2017

The application of compressive sensing (CS) to a radar imaging system based on a frequency-scanned microstrip leaky wave antenna is investigated. First, an analytical model of the system matrix is formulated as the basis for the inversion algorithm. Then, $L_1-norm$ minimization is applied to the inverse problem to generate a range-azimuth image of the scene. Because of the antenna length, the near-field effect is considered in the CS formulation to properly image close-in targets. The resolving capability of the combined frequency-scanned antenna and CS processing is examined and compared to results based on the short-time Fourier transform and the pseudo-inverse. Both simulation and measurement data are tested to show the system performance in terms of image resolution.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.199-202
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• 2002

This parer concerns a design methodology of the observer-based output-feedback digital controller for Takagj-Sugeno (TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.766-773
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• 2001

Omni-directional mobile robots have been popularly employed in several application areas. However, the kinematics for these systems have not been clearly identified, specially for redundantly actuated case which is common in omni-directional mobile robot such as the Nomadic model. For such mobile robot systems, exploitation of redundant actuation as well as singularity analysis has not been extensively addressed. In light of this fact, this paper introduces two different kinematic approaches for omni-directional mobile robots. Then, a singular-free load distribution scheme for redundantly actuated three-wheeled omni-directional mobile robot is proposed. Through simulation, several advantages of redundantly actuated mobile robot in aspect of singularity avoidance, minimization of torque norm, and exploiting several subtasks are presented.

• Journal of the Korean Mathematical Society
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• v.52 no.2
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• pp.349-372
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• 2015

This paper concerns with exploiting an oblique projection technique to solve a general class of large and sparse least squares problem over symmetric arrowhead matrices. As a matter of fact, we develop the conjugate gradient least squares (CGLS) algorithm to obtain the minimum norm symmetric arrowhead least squares solution of the general coupled matrix equations. Furthermore, an approach is offered for computing the optimal approximate symmetric arrowhead solution of the mentioned least squares problem corresponding to a given arbitrary matrix group. In addition, the minimization property of the proposed algorithm is established by utilizing the feature of approximate solutions derived by the projection method. Finally, some numerical experiments are examined which reveal the applicability and feasibility of the handled algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1859-1864
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• 2007

Existing barcode signal restoration algorithms are not robust to unmodeled outliers that may exist in scanned barcode images due to scratches, dirts, etc. In this paper, we describe a robust barcode signal restoration algorithm that uses the hybrid $L_1-L_2$ norm as a similarity measure. To optimze the similarity measure, we propose a modified iterative reweighted least squares algorithm based on the one step minimization of a quadratic surrogate function. In the simulations and experiments with barcode images, the proposed method showed better robustness than the conventional MSE based method. In addition, the proposed method converged quickly during optimization process.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.558-560
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• 1994

In this paper, a memoryless H$_{\infty}$ controller for linear systems with state and input delays is presented. The proposed controller is a delay independent stabilizer which reduces the H$_{\infty}$ norm of the closed loop transfer function, from the disturbance to the controlled output, to a precribed level. The controller is obtained by solving a minimization problem involving linear matrix inequalities.s.

• ETRI Journal
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• v.39 no.1
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• pp.13-20
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• 2017

A method is proposed for scheduling sensor accesses to the shared network in a networked control system. The proposed method determines the access order in which the sensors are granted medium access through minimization of the state estimation error covariance. Solving the problem by evaluating the error covariance for each possible ordered set of sensors is not practical for large systems. Therefore, a convex optimization problem is proposed, which yields approximate yet acceptable results. A state estimator is designed for the augmented system resulting from the incorporation of the optimally chosen communication sequence in the plant dynamics. A car suspension system simulation is conducted to test the proposed method. The results show promising improvement in the state estimation performance by reducing the estimation error norm compared to round-robin scheduling.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.754-759
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• 1992

In this paper, we proposed a mixed H$_{2}$/H$_{\infty}$ optimal controller design method using the parameterization of H$_{2}$ suboptimal controller. The method is based on the minimization of H$_{2}$ performance measure with an H$_{\infty}$-norm constraint. We also derived the necessary and sufficient conditions for existence of solution from the decoupled Riccati equations. And the designed controller has state-space representation.n.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.104-109
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• 2002

A new robust Kalman filter is designed for the linear discrete-time system with norm-bounded parametric uncertainties. Sum quadratic constraint, which describes the uncertainties of the system, is converted into an indefinite quadratic form to be minimized in indefinite inner product space. This minimization problem is solved by the new robust Kalman filter. Since the new filter is obtained by simply modifying the conventional Kalman filter, robust filtering scheme can be more readily designed using the proposed method in comparison with the existing robust Kalman filters. A numerical example demonstrates the robustness and the improvement of the proposed filter compared with the existing filters.

• ETRI Journal
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• v.35 no.2
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• pp.200-206
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• 2013

Most of the literature on compressed sensing has not paid enough attention to scenarios in which the number of acquired measurements is insufficient to satisfy minimal exact reconstruction requirements. In practice, encountering such scenarios is highly likely, either intentionally or unintentionally, that is, due to high sensing cost or to the lack of knowledge of signal properties. We analyze signal reconstruction performance in this setting. The main result is an expression of the reconstruction error as a function of the number of acquired measurements.