• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.339-352
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• 2001

The inverse kinematics problem of Stewart platform is straightforward, but no closed form solution of the forward kinematic problem has been presented. Since we need the real-time forward kinematic solution in MIMO control and the motion monitoring of the platform, it is important to acquire the 6 DOF displacements of the platform from measured lengths of six cylinders in small sampling period. Newton-Raphson method a simple algorithm and good convergence, but it takes too long calculation time. So we reduce 6 nonlinear kinematic equations to 3 polynomials using Nairs method and 3 polynomials to 2 polynomials. Then Newton-Raphson method is used to solve 3 polynomials and 2 polynomials respectively. We investigate operation counts and performance of three methods which come from the equation reduction and Newton-Raphson method, and choose the best method.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1944-1946
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• 2008

This paper analyzed orientation simulation of Stewart platform which is a parallel manipulator of 6-DOF. When platform shape had been given, inverse kinematics as the problem about length of actuator could get an answer using a vector function simply, and forward kinematics as the problem solving shape of platform through the length of actuator could get answer using repetitive and manual explaining Newton-Raphson method because it is expressed a high nonlinear polynomial expression. In addition, for control the Stewart platform it could drive simply and it could confirm the state of orientation in real-time.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.4
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• pp.321-327
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• 1991

Experiments of quenching were made with cylindrical specimens of carbon steel S45C of diameters from 12 to 30mm were performed. The specimens were heated by electric furnace and quenched by immersion method. In order to analyze the temperature profile(cooling curves) of carbon steel including the latent heat of phase transformation, nonlinear heat conduction problem was calculated by the numerical method of inverse heat conduction problem using the apparent heat capacity method. The difference between the calculated and the experimented cooling curves was caused by the latent heat of phase transformation, and the effects of the latent heat were especially manifest at the cooling curves of center of specimens. The temperature and the quantity of the latent heat of phase transformation depend on the cooling speed at A sub(1) transformation point, and the region for cooling speed to become zero was caused by the latent heat of phase transformation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.39.1-39
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• 2001

Impedance tomography (EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents through the electrodes and induced voltages on the surface of the object. We describe a dynamic EIT imaging technique for the case where the resistivity distribution inside the object changes rapidly within the time taken to acquire a full set of independent measurement data, In doing so, the inverse problem is treated as the nonlinear state estimation problem and the unknown state (resistivity) is estimated with the aid of extended Kalman filter in a minimum mean square error sense. In particular, additional electrodes are attached to the known internal structure of the object ...

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.305-309
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• 2004

The problem for parameters estimation of the received signals impinging on array sensors has long been of great research interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition. In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.11
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• pp.9-21
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• 2009

This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.18-24
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• 2009

This paper proposes an analytical method of evaluating the maximum error by modeling the exact tool path for the tool traverse singular region in five-axis machining. It is known that the NC data from the inverse kinematics transformation of 5-axis machining can generate singular positions where incoherent movements of the rotary axes can appear. These lead to unexpected errors and abrupt operations, resulting in scoring on the machined surface. To resolve this problem, previous methods have calculated several tool positions during a singular operation, using inverse kinematics equations to predict tool trajectory and approximate the maximum error. This type of numerical approach, configuring the tool trajectory, requires much computation time to obtain a sufficient number of tool positions in a region. We have derived an analytical equation for the tool trajectory in a singular area by modeling the tool operation into a linear and a nonlinear part that is a general form of the tool trajectory in the singular area and that is suitable for all types of five-axis machine tools. In addition, we have evaluated the maximum tool-path error exactly, using our analytical model. Our algorithm can be used to modify NC data, making the operation smoother and bringing any errors to within tolerance.

• Smart Structures and Systems
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• v.31 no.5
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• pp.437-454
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• 2023

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.293-298
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• 2005

We calculate the coordinates of an axisymmetric nozzle with a central body. This nozzle ensures a transonic flow with a plane sound surface, which is orthogonal to the symmetry axis and has a wall kink at the sonic point, The Chaplygin transformation in the subsonic part of the flow leads the Dirichlet problem for a system of nonlinear equations. The definition domain of the solution in the velocity-hodograph plane is taken as a rectangle. This enables one to obtain the nozzle with a monotonic distribution of velocity along its subsonic part. In the nonlinear differential equation, the linear Chaplygin operator for plane flows is separated, which allows the iterative calculation of the solution. The supersonic part of the nozzle is calculated under the assumption that the flow at the nozzle exit is uniform and parallel to the symmetry axis; i.e., the supersonic jet outflows to the submerged space with the same pressure. The calculation is performed by the characteristic method. The exact solution of Tricomi equation for near-sonic flows with the straight sonic line is used to 'move away' the sound plane. The velocity distribution alone the supersonic part of the nozzle is also monotonic, which ensures the absence of the boundary-layer separation and, therefore, the adequacy of the ideal-gas model. calculations show that the flow in the supersonic part of the nozzle is continuous (compression shocks are absent)

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.329-336
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• 2008

Recently, causality analysis of source time series extracted from EEG or MEG signals is becoming of great importance in human brain mapping studies and noninvasive diagnosis of various brain diseases. Two approaches have been widely used for the analyses: one is independent component analysis (ICA), and the other is multiple signal classification (MUSIC). To the best of our knowledge, however, any comparison studies to reveal the difference of the two approaches have not been reported. In the present study, we compared the performance of the two different techniques, ICA and MUSIC, especially focusing on how accurately they can estimate and separate various brain electrical signals such as linear, nonlinear, and chaotic signals without a priori knowledge. Results of the realistic simulation studies, adopting directed transfer function (DTF) and Granger causality (GC) as measures of the accurate extraction of source time series, demonstrated that the MUSIC-based approach is more reliable than the ICA-based approach.