• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.33-38
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• 2002

In this paper, a Two-Degree-of-Freedom-Controller(TDFC) for DC motors based on inverse dynamics and the fuzzy technique is presented. The proposed controller includes the inverse dynamic model of a DC motor system, a prefilter and a fuzzy compensator. The model of the system is characterized by a nonlinear equation with coulomb friction. The prefilter eliminates high frequency effects occurring when the inverse dynamic model is implemented. The fuzzy compensator is designed for tracking the change of the reference input and simultaneously regulating the error between the reference input and the system output which can be caused by disturbances. The optimal parameters of both the model and the compensator are identified by a real-coded genetic algorithm. An experimental work on a DC motor system is carried out to verify the performance of the proposed controller.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.957-968
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• 2021

Inverse censoring probability weighting (ICPW) is a popular technique in survival data analysis. In applications of the ICPW technique such as the censored regression, it is crucial to accurately estimate the censoring probability. A simulation study is undertaken in this article to see how censoring probability estimate influences model performance in censored regression using the ICPW scheme. We compare three censoring probability estimators, including Kaplan-Meier (KM) estimator, Cox proportional hazard model estimator, and local KM estimator. For the local KM estimator, we propose to reduce the predictor dimension to avoid the curse of dimensionality and consider two popular dimension reduction tools: principal component analysis and sliced inverse regression. Finally, we found that the Cox proportional hazard model estimator shows the best performance as a censoring probability estimator in both mean and median censored regressions.

• Structural Engineering and Mechanics
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• v.28 no.5
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• pp.525-548
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• 2008

This article deals the theory for solving an inverse problem of plate structures using the frequency-domain information instead of classical time-domain delays or free vibration eigenmodes or eigenvalues. A reduced set of output parameters characterizing the defect is used as a regularization technique to drastically overcome noise problems that appear in imaging techniques. A deconvolution scheme from an undamaged specimen overrides uncertainties about the input signal and other coherent noises. This approach provides the advantage that it is not necessary to visually identify the portion of the signal that contains the information about the defect. The theoretical model for Quantitative nondestructive evaluation, the relationship between the real and ideal models, the finite element method (FEM) for the forward problem, and inverse procedure for detecting the defects are developed. The theoretical formulation is experimentally verified using dynamic responses of a steel plate under impact loading at several points. The signal synthesized by FEM, the residual, and its components are analyzed for different choices of time window. The noise effects are taken into account in the inversion strategy by designing a filter for the cost functional to be minimized. The technique is focused toward a exible and rapid inspection of large areas, by recovering the position of the defect by means of a single accelerometer, overriding experimental calibration, and using a reduced number of impact events.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1806-1813
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• 2002

It is well known 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, a classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select a trial solution initially for optimization because the defined objective function is heavily multimodal. A method is presented in this paper, which uses continuous evolutionary algorithms(CEAs). CEAs are effective for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising with high parallel efficiency over about 94%.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.684-689
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• 2003

One field identified by an inverse method is one of multiple candidate solutions those are independently obtained through a specific estimation technique. While averaging of optimized fields can provide a better description of the spatial feature of an unknown field, it deteriorates the flow and transport characteristics of the optimized fields. As a result, the averaged field is not suited for modeling aquifer performances. Based on genetic algorithm, an optimal field synthesis technique is developed, which combines diversely optimized fields into a refined group of fields. Each field in the population is paired, and a sub-region of each field is exchanged by crossover operation to create a group of synthesized fields of enhanced modeling capability. The population of the fields is evolved till the synthesized fields become sufficiently similar. Applications of the optimal field synthesis to synthetic cases indicate that the objective functions of the fields assessing the modeling capabilities are further reduced after the optimal field synthesis. The identified fields from various inverse techniques may yield a range of modeling results under varied flow situations. The uncertainty is narrowed down through the optimal field synthesis and the associated modeling results converge on that of the reference field. The developed inverse modeling facilitates the construction of a reliable simulation model and hence trustworthy predictions of the future performances.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.632-639
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• 2004

In this paper, an inverse problem of glass forming process is studied to determine a number of unknown heat transfer coefficients which are imposed as boundary conditions. An analysis program for transient heat conduction of axi-symmetric dimension is developed to simulate the forming and cooling process. The analysis is repeated until it attains periodic state, which requires at least 30 cycles of iteration. Measurements are made for the temperatures at several available time and positions of glass and moulds in operation. Heat removal by the cooling water from the plunger is also recorded. An optimization problem is formulated to determine heat transfer coefficients which minimize the difference between the measured data and analysis results. Significant time savings are achieved in finite difference based sensitivity computation during the optimization by employing distributed computing technique. The analysis results by the optimum heat transfer coefficients are found to agree well with the measured data.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.862-868
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• 2007

The planar motion of the index finger in general human hands is usually implemented by the actuation of three joints. This task requires a technique to determine the joint combination for each fingertip position which is well-known as the inverse kinematics problem in robotics. Especially, it is an essential work for grasping and manipulation tasks by robotic and humanoid fingers. In this paper, an intelligent neural learning scheme for solving such inverse kinematics is presented. Specifically, a multi-layered neural network is utilized for effective inverse kinematics, where a dynamic neural learning algorithm is employed for fast learning. Also, a bio-mimetic feature of general human fingers is incorporated to the learning scheme. The usefulness of the proposed approach is verified by simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.199-202
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• 1997

In this paper, a novel disturbance observer is proposed in order to regulate the disturbance in motor systems. The proposed observer does not require the implementation of ideal derivative of the state since the inverse of the nominal model is not used in the design of the observer. The transfer gain from a disturbance to the output of the disturbance observer is one. So, there is no time-delay in the response due to the dynamics of the observer.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.331-336
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• 1986

Because the threshold technique using the histogram of intensity is the most attractive for segmentation in the sense of fast image processing, this paper defined the new function of inverse histogram of intensity and found out a threshold by means of it. The segmented errors are removed by regulating a scan size of blob coloring. Blob-coloring algorithm presented by [6] was reproved for good performance i.e., no change of feature in bolobs after blob coloring. The ratio of successful recognition was about 85 percents.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.3
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• pp.321-328
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• 1996

This paper presents a robot simulator which can automatically generate a smooth collision free path. This simulator has the characterstisc of the object - oriented programming which is coded in Borland C+ +. Using General Inverse Algorithm, the inverse kinematics solutions of any kind of robots can be found generally. This simulator also uses Bezier Functions for the description of a smooth collision - free path. In addition, GUI(Graphic User Interface)technique is employed for user's convenience.