• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.177-182
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• 1994

In this paper, an output feedback adaptive variable structure control scheme is presented for stabilization of large scale power systems. An additional input signal which is called a power system stabilizer(PSS) is needed to improve the stability of a power system and to maintain the synchronization of generators. The proposed PSS scheme does not require a priori knowledge of uncertainty bounds. It is guaranteed that the closed-loop system is globally uniformly ultimately bounded by the Lyapunov stability theory. Simulation results for a multimachine power system are given to show the feasibility of the proposed scheme and the superiority of the proposed PSS in comparison with the conventional lead-lag PSS of PID-type.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.39-43
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• 1989

In this paper, the concept of ultrasonic transmission imaging system with crossed -arrays is Introduced. The crossed-array system is simulated by angular spectrum method In the operating frequency of 12MHz. A theoritical development of a system transfer function matrix 1M is presented. Using this matrix, a priori knowledge on the physical properties of the system is understood. It proves to be a block Toeplitz matrix with Toeplitz entries. Using the Inversion procedure, the spatial degradations of the measured image can be removed.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.539-544
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• 2009

An estimation of 3D velocity field including occluded parts without maxing tracer to the fluid had not only never been proposed but also impossible by the conventional computer vision algorithm. In this paper, we propose a new method of three dimensional optical flow of the fluid based on physical model, where some boundary conditions are given from a priori knowledge of the flow configuration. Optical flow is obtained by minimizing the mean square errors of a basic constraint and the matching error terms with visual data using Euler equations. Here, Navier-Stokes motion equations and the differences between occluded data and observable data are employed as the basic constrains. we verify the effectiveness of our proposed method by applying our algorithm to simulated data with partly artificially deleted and recovering the lacking data. Next, applying our method to the fluid of observable surface data and the knowledge of boundary conditions, we demonstrate that 3D optical flow are obtained by proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.8
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• pp.557-562
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• 1988

This paper presents a class of discrete adaptive controller that can be applied to a plant without sufficient a priori information. It is well known that the GMV(Generalized Minmum Variance) contrlller performs satisfactorily if the plant time delay is known. By introducing the long-range prediction into the GMV controller, robustness to the time delay can be improved, although optimality is lost. Such an idea motivates a predictive control system to be proposed here, where the system minimizes multi-stage cost via the GMV approach. Moreover, the detuning control weight is determined by an on-line tuning method. It is shown that robustness, computational efficiency, and performance of the resulting control system are improved as compared with those of the GPC(Generalized Predictive Control)system.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.486-495
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• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.63.3-63
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• 2001

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. In this paper, we propose a three dimensional volume reconstruction method, which is an iterative method and as uniform and simulated algebraic reconstruction technique (USART). In this method, two or more x-ray images projected from different views are needed, and also the geometry of the imaging system need to be a priori identified well. That is to say, the relative locations between the x-ray source, imaging plane and the object should be determined exactly by calibration. To achieve this, we propose a series of coordinate calibration methods of the x-ray imaging system using grid pattern images. Some experimental results of these calibrations is presented and discussed in detail ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.63.4-63
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• 2001

An x-ray vision can be a unique method to monitor and analyze the motion of mechanical parts in real time which are invisible from outside. Our problem is to identify the pose, i.e. the position and orientation of an object from x-ray projection images. It is assumed here that the x-ray imaging conditions that include the relative coordinates of the x-ray source and the image plane are predetermined and the object geometry is known. In this situation, an x-ray image of an object at a given pose can be estimated computationally by using a priori known x-ray projection image model. It is based on the assumption that a pose of an object can be determined uniquely to a given x-ray projection image. Thus, once we have the numerical model of x-ray imaging process, x-ray image of the known object at any pose could be estimated ...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.4-41
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• 2002

In this paper we deal with visual servoing that can control a robot arm with a camera using information of images only, without estimating 3D position and rotation of the robot arm. Here it is assumed that the robot arm is calibrated and the camera is uncalibrated. Here we consider two coordinate systems, the world coordinate system and the camera coordinate one and we use a pinhole camera model as the camera one. First of all, the essential notion can be show, that is, epipolar geometry, epipole, epipolar equation, and epipolar constrain. And these plays an important role in designing visual servoing in the later chapters. Statement of the problem is giver. Provided two a priori...

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.1-28
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• 2004

We first apply a first order splitting to a semilinear reaction-diffusion equation and then discretize the resulting system by an $H^1$-Galerkin mixed finite element method in space. This semidiscrete method yields a system of differential algebraic equations (DAEs) of index one. A priori error estimates for semidiscrete scheme are derived for both differ-ential as well as algebraic components. For fully discretization, an implicit Runge-Kutta (IRK) methods is applied to the temporal direction and the error estimates are discussed for both components. Finally, we conclude the paper with a numerical example.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1670-1679
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• 1995

In this paper, an optimal variable structure controller with a multilayer neural inverse identifier is proposed. A multilayer neural network with error back propagation learning algorithm is used for construction the neural inverse identifier which is an observer of the external disturbances and the parameter variations of the system. The variable structure controller with the multilayer neural inverse identifier not only needs a small part of a priori knowledge of the bounds of external disturbances and parameter variations but also alleviates the chattering magnitude of the control input. Also, an optimal sliding line is designed by the optimal linear regulator technique and an integrator is introduced for solving the reaching phase problem. Computer simulation results show that the proposed approach gives the effective control results by reducing the chattering magnitude of control input.