• Nuclear Engineering and Technology
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• 제52권11호
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• pp.2630-2637
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• 2020

The structure design of divertor Multi-Functional Maintenance Platform (MFMP) actuated by hydraulic system for China Fusion Engineering Test Reactor (CFETR) was introduced in this paper. The model of MFMP was established according to maintenance requirements. In this paper, Newton-Euler method and the improved virtual work principle were used, the equivalent driving force of each actuator was obtained through the equivalent Jacobian inverse matrix derived from velocity relationship among the components. The accuracy of the model was verified by ADAMS simulation. The stability control of the heavy-duty components driven by hydraulic cylinders based on Newton-Euler method and improved virtual work principle was established.

• Smart Structures and Systems
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• 제31권4호
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• pp.409-419
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• 2023

Structural integrity can be accessed from dynamic deformations of structures. Moreover, dynamic deformations can be acquired from non-contact sensors such as video cameras. Kanade-Lucas-Tomasi (KLT) algorithm is one of the commonly used methods for motion tracking. However, averaging throughout the extracted features would induce bias in the measurement. In addition, pixel-wise measurements can be converted to physical units through camera intrinsic. Still, the depth information is unreachable without prior knowledge of the space information. The assigned homogeneous coordinates would then mismatch manually selected feature points, resulting in measurement errors during coordinate transformation. In this study, a two-stage optimization method for video-based measurements is proposed. The manually selected feature points are first optimized by minimizing the errors compared with the homogeneous coordinate. Then, the optimized points are utilized for the KLT algorithm to extract displacements through inverse projection. Two additional criteria are employed to eliminate outliers from KLT, resulting in more reliable displacement responses. The second-stage optimization subsequently fine-tunes the geometry of the selected coordinates. The optimization process also considers the number of interpolation points at different depths of an image to reduce the effect of out-of-plane motions. As a result, the proposed method is numerically investigated by using a truss bridge as a physics-based graphic model (PBGM) to extract high-accuracy displacements from recorded videos under various capturing angles and structural conditions.

• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.312-317
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• 1996

This paper proposes a neural network controller with the computed torque method. The neural network is used not to learn the inverse dynamic model but to compensate the uncertainties of robotic manipulators. When training the neural network, we use the signals present in the proposed controller, which is simpler than that proposed by Ishiguro et al., whose teaching signals of the neural network come from the robot model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.698-701
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• 1996

A novel neural network control scheme is proposed to identify the inverse dynamic model of robot manipulator and to compensate for uncertainties in robot dynamics. The proposed controller is called reference compensation technique(RCT) by compensating at reference input trajectory. The proposed RCT scheme has many benefits due to the differences in compensating position and learning algorithm. Since the compensation is done outside the plant it can be applied to many control systems without modifying the inside controller. It performs well with low controller gain because the operating range of input values is small and the output of the neural network controller is amplified through the controller gain. The back-propagation algorithm is used to train and simulations of three link robot manipulator are carried out to prove the proposed controller's performances.

• Journal of Mechanical Science and Technology
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• 제20권5호
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• pp.591-601
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• 2006

In this paper, we present a new control methodology for perturbed crane systems. Nonlinear crane systems are transformed to linear models by feedback linearization. An inverse dynamic equation is applied to compute the system PD control force. The PD control parameters are selected based on a nominal model and are therefore suboptimal for a perturbed system. To achieve the desired performance despite model perturbations, we construct a neural network auxiliary controller to compensate for modeling errors and disturbances. The overall control input is the sum of the nominal PD control and the neural auxiliary control. The neural network is iteratively trained with a perturbed system until acceptable performance is attained. We apply the proposed control scheme to 2- and 3-degree-of-freedom (D.O.F.) crane systems, with known bounds on the payload mass. The effectiveness of the control approach is numerically demonstrated through computer simulation experiments.

• 한국정밀공학회지
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• 제20권12호
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• pp.80-88
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• 2003

We propose a new technique to design an unmaned integrating control system based-on Windows XP version off-Line Programming System which can simulate a dynamic model of robot manipulator in three dimensions graphics space in this paper. The robot with 4 and 6 axes modeled SM5 and AM1 respectively were adopted as an objective model. Forward kinematics, inverse kinematics and robot dynamics modeling were included in the developed off-line program. The interface between users and the off$.$line programming system in the Windows XP's graphic user interface environment was also studied. The developing language is Microsoft Visual C++. Graphic libraries, OpenGL, by silicon Graphics, Inc. were utilized for three dimensions graphics.

• 통합자연과학논문집
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• 제1권2호
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• pp.127-132
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• 2008

This project follows the heterogeneous agent market segmented model of Landon-Lane and Occhino (2007) with using Korean data, M1 and GDP deflator from 1882:I to 2007:II. This paper estimates parameters with Monte Carlo Markov Chain. The fraction of traders, ${\lambda}$, in Korea is 15.64%. The quarterly preferences discount factor's, ${\beta}$, posterior mean is 0.9922. The posterior mean of the inverse of the elasticity of the labor supply to the real wage, ${\varphi}$, is 0.0316. The elasticity of the labor supply to the real wage has a very large value. By Hansen (1985) and Christiano and Eichenbaum (1992) and Cooley and Hansen (1989), models having large elasticity of the aggregate labor supply better match macroeconomic data.

• 전기의세계
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• 제31권3호
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• pp.204-208
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• 1982

The objective of this paper is to present a digital method for improving the lateral resolution of the B-scan images in the medical applications of ultrasound. The method is based upon a mathematical model of the lateral blurring caused by the finite beam width of the transducers. This model provides a simple method of applying a recursive scheme for image restoration with fast computation time. The point spread function (P.S.F.) can be measured by the reflective signals after scanning the small pins located along the depth of interest. From the measured P.S.F., one can compute the coefficient matrices of the inverse discrete-time dynamic state variable equation of the blurring process. Then, a recursive scheme for deblurring is applied to the recorded B-scan to improve the lateral resolution. One major advantage of the present recursive scheme over the transform method is in its applicability for the space-variant imaging, such as in the case of the rotational movement of transducer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.221-223
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• 1993

The Hopfield model is defined as an adaptive dynamic system. In this paper we propose a modified neural network which is capable of solving linear programming problems and a set of linear equations. The model is directly implemented from the given system, and solves the problem without calculating the inverse of the matrices. We get the better stability results by the addition of scaling property and by using the nonlinearities in the linear programming neural networks.

• 대한기계학회논문집A
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• 제24권1호
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• pp.190-195
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• 2000

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure. Nikolakopoulos et. al. used the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However the intersecting point of the superposed contours is not only difficult to find but also incorrect to calculate. A method is presented in this paper which uses optimization technique for the location and depth of the crack. The basic idea is to find parameters which use the structural eigenfrequencies on crack depth and location and optimization algorithm. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. Method of optimization is augmented lagrange multiplier method and search direction method is BFGS variable metric method and one dimensional search method is polynomial interpolation.