• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.27-40
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• 1996

This paper proposed a kinematic modeling methodlogy and feedback control system based on kinematics for 2 degrees of freedom of 4-wheeled mobile robot. We assigned coordinate systems to specify the transformation matirx and write the kinematic equation of motion. We derived the actuated inverse and sensed forwared solution for the calculation of actual robot orientation and the desired robot orientation. It is the most significant error and has the largest impact on the motion accuracy. To calculate the WMR position in real time, we introduced the dead-reckoning algorithm and composed two feedback control system that is based on kinematics. Through the simulation result, we compare with the ffedback control system for position control.

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.538-544
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• 2003

Although many methodologies exist for determining the constrained equations of motion, most of these methods depend on numerical approaches such as the Lagrange multiplier's method expressed in differential/algebraic systems. In 1992, Udwadia and Kalaba proposed explicit equations of motion for constrained systems based on Gauss's principle and elementary linear algebra without any multipliers or complicated intermediate processes. The generalized inverse method was the first work to present explicit equations of motion for constrained systems. However, numerical integration results of the equation of motion gradually veer away from the constraint equations with time. Thus, an objective of this study is to provide a numerical integration scheme, which modifies the generalized inverse method to reduce the errors. The modified equations of motion for constrained systems include the position constraints of index 3 systems and their first derivatives with respect to time in addition to their second derivatives with respect to time. The effectiveness of the proposed method is illustrated by numerical examples.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.1
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• pp.1-12
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• 1991

In this paper the design and construction of discrete model following servo dontroller on the position control system is proposed. The operational time delay of the plant in the controller which is proposed, is considered and the system which is added by the integral compensation in first order difference equation is constructed. By applying the optimal regulator method to the system, the method which find the optimal state feedback gain is developed theoretically. The output of a model which is correspond to a DC Servo motor follow quickly the speed response of a DC Servo motor and the velocity error in ansteady-state is reduced in zero and the position response is controlled correctly, the performance of the controller is contoller is confirmed by Computer Simulation.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2521-2524
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• 2003

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors (accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range missile missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System (SDINS) using Line-Of-Sight(LOS) vector from star sensor. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the bounded-ness of position and attitude errors.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.329-336
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• 2007

This paper considers a fault accommodation problem for inertial navigation systems (INS) that have redundant inertial sensors such as gyroscopes and accelerometers. It is wellknown that the more sensors are used, the smaller the navigation error of INS is, which means that the error covariance of the position estimate becomes less. Thus, when it is decided that double faults occur in the inertial sensors due to fault detection and isolation (FDI), it is necessary to decide whether the faulty sensors should be excluded or not. A new accommodation rule for double faults is proposed based on the error covariance of triad-solution of redundant inertial sensors, which is related to the navigation accuracy of INS. The proposed accommodation rule provides decision rules to determine which sensors should be excluded among faulty sensors. Monte Carlo simulation is performed for dodecahedron configuration, in which case the proposed accommodation rule can be drawn in the decision space of the two-dimensional Cartesian coordinate system.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• Journal of the Korean School Mathematics Society
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• v.12 no.3
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• pp.267-289
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• 2009

Students have difficulties in solving linear equation problems with a variable on the right side rather than linear equation problems a variable on the left side of the sign of equality. In order for students to overcome such difficulties, opportunities to experience many types of basic linear equation problems would have to be provided. Also, it is necessary to examine the process of students' problem solving process by constructing various types of evaluation item and test them in instruction and learning of linear equations, or grasp students' studying statues through individual interview and based on theses, error correction through feedbacks have to be achieved.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.347-353
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• 2019

Electric-hydraulic sever cylinders are used in many offshore applications such as wind energy farms, solar farms and plants. Jack-up barges are often used for these offshore system operations. Jack-up barge control is up/down by hydraulic cylinder position control. Working in harsh environments can lead to changes in internal parameters. This nonlinearity makes precise control difficult. In order to overcome the problems, we proposed a method of unknown-parameter estimation algorithm based on measurements obtained by system. In this paper, we employee Unscented Kalman filter (UKF) to estimate states and unknown-parameter from augmented nonlinear equation. Performance of estimation results is verified in simulation on an environments of Matlab. The estimation results of the state and unknown-parameter show that the estimation error of unknown-parameter is reduced according to decreasing the state estimation error.

• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.21-46
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• 2011

The natural frequencies of continuous systems depend on the governing partial differential equation and can be numerically estimated using the finite element method. The accuracy and convergence of the finite element method depends on the choice of basis functions. A basis function will generally perform better if it is closely linked to the problem physics. The stiffness matrix is the same for either static or dynamic loading, hence the basis function can be chosen such that it satisfies the static part of the governing differential equation. However, in the case of a rotating beam, an exact closed form solution for the static part of the governing differential equation is not known. In this paper, we try to find an approximate solution for the static part of the governing differential equation for an uniform rotating beam. The error resulting from the approximation is minimized to generate relations between the constants assumed in the solution. This new function is used as a basis function which gives rise to shape functions which depend on position of the element in the beam, material, geometric properties and rotational speed of the beam. The results of finite element analysis with the new basis functions are verified with published literature for uniform and tapered rotating beams under different boundary conditions. Numerical results clearly show the advantage of the current approach at high rotation speeds with a reduction of 10 to 33% in the degrees of freedom required for convergence of the first five modes to four decimal places for an uniform rotating cantilever beam.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.65-71
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• 2020

In order to accurately track the trajectory of the smartphone indoors and outdoors, the WiFi Fingerprint method and the Pedestrian Dead Reckoning method are fused. The former can estimate the absolute position, but an error occurs randomly from the actual position, and the latter continuously estimates the position, but there are accumulated errors as it moves. In this paper, the model and Kalman Filter equation to fuse the estimated position data of the two methods were established, and optimal system parameters were derived. According to covariance value of the system noise and measurement noise the estimation accuracy is analyzed. Using the measured data and simulation, it was confirmed that the improved performance was obtained by complementing the two methods.