• Journal of Biomedical Engineering Research
• /
• v.25 no.4
• /
• pp.301-307
• /
• 2004

An inverse dynamic model of lower limbs is presented to calculate joint moments during gait. The model is composed of 4 segments with 3 translational joints and 12 revolute joints. The inverse dynamic method is based on Newton-Euler formalism. Kinematic data are obtained from 3 dimensional trajectories of markers collected by a motion analysis system. External forces applied on the foot are measured synchronously using force plate. The use of developed model makes it possible to calculate joint moments for variation of parameters.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.5
• /
• pp.442-448
• /
• 2000

The conventional control of dynamic systems needs accurate mathematical modeling of control systems. But the modeling of dynamic systems require very complex computation process due to complex state equation and many control parameters. Accordingly this paper proposes a state space identification model of the dynamic system using neural networks. The Gauss-Newton method is used to train the proposed neural network and the effectiveness of proposed method is verified through the computer simulation of the Seesaw system identification problem.

• Proceedings of the KSME Conference
• /
• 2000.04a
• /
• pp.339-344
• /
• 2000

Newton-Raphson 기법은 구조물의 비선형 해석에 널리 쓰이는 반복계산기법이다. 비선형 해석을 위한 반복계산기법은 컴퓨터의 발달을 감안해도 상당한 계산시간이 소요된다. 본 논문에서는 신경회로망 예측을 사용한 Predicted Newton-Raphson 반복계산기법을 제안하였다. 통상적인 Newton-Raphson 기법은 이전스텝에서 수렴된 점으로부터 현재 스텝의 반복계산을 시작하는 반면 제시된 방법은 현재 스텝 수렴해에 대한 예측점에서 반복계산을 시작한다. 수렴해에 대한 예측은 신경회로망을 사용하여 이전 스텝 수렴해의 과거경향을 파악한 후 구한다. 반복계산 시작점이 수렴점에 보다 근접하여 위치하므로 수렴속도가 빨라지게 되고 허용되는 하중스텝의 크기가 커지게 된다. 또한 반복계산의 시작점으로부터 이루어지는 계산과정은 통상적인 Newton-Raphson 기법과 동일하므로 기존의 Newton-Raphson 기법과 정확히 일치하는 수렴해를 구할 수 있다. 구조물의 정적 비선형 거동에 대한 수치해석을 통하여 modified Newton-Raphson 기법과 제시된 Predicted Newton=Raphson 기법의 정확성과 효율성을 비교하였다. 제시된 Predicted Newton-Raphson 기법은 modified Newton-Raphson 기법과 동일한 해를 산출하면서도 계산상의 효율성이 매우 큼을 확인할 수 있었다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2006.11a
• /
• pp.135-138
• /
• 2006

We developed an engine system design program by balancing the pressure-mass-power relation which can be acquired from each component's specification. In gas generator type open-cycle rocket engine system it is possible to distinguish the variables into two categories, which are input variables and requirement variables. We define 11 design variables corresponding to the 11 balance equations as functions of pressure, mass and power of target engine system. We solved these equations by Newton method. As an example we designed gas generator cycle engine system and finally we could conclude that this developed program is well suited to the engine system design.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.11a
• /
• pp.366-370
• /
• 2008

Mode analysis is very important for the development of liquid rocket engine in various applications. We developed a mode analysis program for the gas-generator cycle liquid rocket engine by proposing 13 independent equations with 13 independent variables which can be solved by Newton method. As an example we calculated the change of engine operating mode according to the control valve's loss coefficient change located in the gas-generator oxidizer supply line. And we concluded that this program can give basic idea for the mode analysis of gas-generator cycle liquid rocket engine.

• Journal of IKEEE
• /
• v.19 no.2
• /
• pp.219-224
• /
• 2015

Electrical impedance tomography is an imaging technique to reconstruct the internal conductivity distribution based on applied currents and measured voltages in a domain of interest. In this paper, a modified Gauss-Newton method is proposed for conductivity image reconstruction. In the proposed method, the dimension of the inverse term is reduced by replacing the number of elements with the number of measurement data in the conductivity updating equation of the conventional Gauss-Newton method. Therefore, the computation time is greatly reduced as compared to the conventional Gauss-Newton method. Moreover, the regularization parameter is selected by computing the minimum-maximum from the diagonal components of the Jacobian matrix at every iteration. The numerical experiments with several scenarios were carried out to evaluate the reconstruction performance of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.40 no.6
• /
• pp.347-355
• /
• 2016

This study presents a Lattice Boltzmann Method (LBM) coupled with a momentum-exchange approach/fictitious domain (MEA/FD) method for the simulation of particle suspensions. The method combines the advantages of the LB and the FD methods by using two unrelated meshes, namely, a Eulerian mesh for the flow domain and a Lagrangian mesh for the solid domain. The rigid body conditions are enforced by the momentum-exchange scheme in which the desired value of velocity is imposed directly in the particle inner domain by introducing a pseudo body force to satisfy the constraint of rigid body motion, which is the key idea of a fictitious domain (FD) method. The LB-MEA/FD method has been validated by simulating two different cases, and the results have been compared with those through other methods. The numerical evidence illustrated the capability and robustness of the present method for simulating particle suspensions.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.4
• /
• pp.447-459
• /
• 2013

Many problems need to be solved before vision systems can actually be applied in industry, such as the precision of the kinematics model of the robot control algorithm based on visual information, active compensation of the camera's focal length and orientation during the movement of the robot, and understanding the mapping of the physical 3-D space into 2-D camera coordinates. An algorithm is proposed to enable robot to move actively even if the relative positions between the camera and the robot is unknown. To solve the correction problem, this study proposes vision system model with six camera parameters. To develop the robot vision control algorithm, the N-R and EKF methods are applied to the vision system model. Finally, the position accuracy and processing time of the two algorithms developed based based on the EKF and the N-R methods are compared experimentally by making the robot perform slender bar placement task.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.8
• /
• pp.99-106
• /
• 2017

Electrical impedance tomography is a nondestructive imaging modality in which the internal resistivity distribution is reconstructed based on the injected currents and measured voltages inside a domain of interest. In this paper, an adaptive threshold value based region of interest (ROI) method is proposed to improve the spatial resolution of reconstructed images as well as to reduce the computational time of the inverse problem. Adaptive threshold value is calculated by INTERMODES method and ROI is determined from the domain based on this value. Moreover, the computational domain of image reconstruction is restricted within a ROI and iterative Gauss-Newton method is employed to estimate the resistivity distribution. To evaluate the performance of the proposed method, numerical experiments have been performed and the results are analyzed.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.40 no.3
• /
• pp.305-315
• /
• 2016

This study aims to develop a robot vision control scheme using the Newton-Raphson (N-R) method for the uncertainty of circumstance caused by the appearance of obstacles during robot movement. The vision system model used for this study involves six camera parameters (C1-C6). First, the estimation scheme for the six camera parameters is developed. Then, based on the six estimated parameters for three of the cameras, a scheme for the robot's joint angles is developed for the placement of a slender bar. For the placement of a slender bar for the uncertainty of circumstances, in particular, the discontinuous robot trajectory caused by obstacles is divided into three obstacle regions: the beginning region, middle region, and near-target region. Then, the effects of obstacles while using the proposed robot vision control scheme are investigated in each obstacle region by performing experiments with the placement of the slender bar.