• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.248-254
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• 1996

A disturbance rejection controller using eccentricity filtering and LQ control techniques is proposed to alleviate significantly the effect of roll eccentricity in multivariable cold-rolling processes. Fundamental problems such as process time delay inherent in exit thickness measurement and non-stationary characteristics of roll eccentricity signals can be overcome by the proposed control method. The filtered instantaneous estimate of roll eccentricity may be exploited to improve instantaneous estimate of the exit thickness variation based on roll force and roll gap mearsurements, and a feedforward compensator is augmented as a reference for a gaugemeter thickness estimator. And, LQ feedback controller is combined with eccentricity filter for the attenuation of the exit thickness variation due to the entry thickness variation. The simulation results show that eccentricity components have been significantly eliminated and simultaneously other distrubances also have been attenuated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.7
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• pp.659-666
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• 2016

Magnetic disturbance is one of the main factors that deteriorate the accuracy of orientation estimation methods based on inertial/magnetic sensor signals. This paper proposes a parallel Kalman filter(KF) that explicitly detects magnetic disturbances and thus can accurately estimate 3D orientation in magnetically disturbed environments. Due to the parallel nature of the proposed KF, even severe magnetic disturbances only affect yaw estimation, while roll and pitch values remain accurate. Consequently, the proposed KF can be effectively used in various applications that involve magnetically inhomogeneous environments, such as robots, ships, and planes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.221-228
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• 2014

In this paper, the operational concept and the navigation algorithms for the gliding guided artillery munition are studied. The gliding guided artillery munition has wings for gliding; therefore spin of the munition should be eliminated. The previous navigation algorithms assumed a spinning munition with constant angular velocity; hence, they cannot be applied for the gliding munition. Moreover, lateral stability becomes worse due to decrease of angular momentum. Therefore, side force should be controlled to improve the stability, and the munition should maneuver, then the previous navigation algorithms for typical fixed-wing aircraft cannot be applied. In this paper, we apply the previous navigation algorithms for the spinning munition. Spin is eliminated and wings are deployed based on the estimation results, and the advanced navigation algorithm for the non-spinning munition is introduced.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.927-933
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• 2020

This paper presents a fuel quantity measurement system (FQMS) for an aircraft supplementary fuel tank considering the change of aircraft attitude. The developed FQMS consists of fuel sensors, a signal process unit, an indicator and a software to estimate the fuel quantity from the sensor data. To replicate the change of the roll and pitch attitude on the ground, the test simulator is developed in this work. Using the test simulator, the sensor data at various fuel quantities, roll and pitch angles are automatically measured to build a training data set. The data-driven software to estimate the fuel quantity is then developed using a trilinear interpolation method with the training data set. The developed FQMS is verified by investigating the fuel estimation error of the test data set that we know the true values. Through the test, it is confirmed that the error of the developed FQMS system satisfies the criteria of TSO-C55 document.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.453-461
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• 2013

This paper describes evaluation procedures and experimental results for the estimation of Cumulative Distribution Functions (CDF) giving best-fit to the sample data in the Probability based risk Evaluation Techniques (PET) which is to assess the risks of a small-sized sea floater. The CDF in the PET is to provide the reference values of risk acceptance criteria which are to evaluate the risk level of the floater and, it can be estimated from sample data sets of motion response functions such as Roll, Pitch and Heave in the floater model. Using Maximum Likelihood Estimates and with the eight kinds of regulated distribution functions, the evaluation tests for the CDF having maximum likelihood to the sample data are carried out in this work. Throughout goodness-of-fit tests to the distribution functions, it is shown that the Beta distribution is best-fit to the Roll and Pitch sample data with smallest averaged probability errors $\bar{\delta}(0{\leq}\bar{\delta}{\leq}1.0)$ of 0.024 and 0.022, respectively and, Gamma distribution is best-fit to the Heave sample data with smallest $\bar{\delta}$ of 0.027. The proposed method in this paper can be expected to adopt in various application areas estimating best-fit distributions to the sample data.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.135-142
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• 2018

In recent years, researches utilizing UAV for military purposes such as precision tracking and batting have been actively conducted. In order to track the preceding flight, there has been a previous research on estimating the attitude information of the flight such as roll, pitch, and yaw using images taken from the rear UAV. In this study, we propose a method to estimate the attitude information more precisely by applying the Kalman filter to the existing image processing technique. By applying the Kalman filter to the estimated attitude data using image processing, we could reduce the estimation error of the attitude angle significantly. Through the simulation experiments, it was confirmed that the estimation using the Kalman filter can estimate the posture information of the aircraft more accurately.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.6
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• pp.31-38
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• 2002

This paper presents the analysis of the flight test data measured by the sensors installed on a four-seat canard aircraft. The inherent stall proof characteristics of canard aircraft was verified from the stall test. The dihedral effect, adverse yaw and roll control power were examined and the neutral point that determines the longitudinal stability of the aircraft was investigated. The dynamic characteristics such as dutch roll mode were also examined. Without relying on the parameter identification method, the aerodynamic derivatives or the relations between the aerodynamic derivatives were obtained by analyzing the steady state flight data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.7
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• pp.529-536
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• 2020

Reaction Control System of the third stage of the Korean Space Launch Vehicle II conducts roll control and 3 axis control throughout third stage engine start, satellite separation, and collision and contamination avoidance maneuver. Reaction control system consumes its propellant in each thruster operation. Hence, loading of proper amount of the propellant is important for mission success. It is needed to have a rough estimation method of propellant consumption during the flight. In this paper, we developed a energy equation using pressure and temperature data which are acquired in the on-board reaction control system. We constructed a test system which is similar with the on-board reaction control system to verify the energy equation. Test results using deionized water were compared with estimated propellant consumption. We also conducted an error analysis of the energy equation. We also presented the propellant consumption result of a system level operation test.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.783-789
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• 2017

In terms of 3D orientation estimation based on nine-axis IMMU(inertial and magnetic measurement unit), there are two disturbance components decreasing estimation accuracy: one is external acceleration disturbing accelerometer's signals and the other is magnetic disturbance related to magnetometer's signals. In order to minimize effects by these two disturbances, two approaches including switching approach and model-based approach have been suggested and further research comparing these two has also been conducted. Nevertheless, effect of disturbance modeling differences on orientation estimation accuracy in model-based approach has not been studied before. This paper compares the recently reported two orientation estimation algorithms that have difference in disturbance models, in order to investigate the effect of disturbance models on accuracy of IMMU-based orientation estimation under various operating conditions. This research shows that the difference in disturbance models leads to difference in process noise covariance matrix. Consequently, this affected the orientation estimation, i.e., the estimation differences between the algorithms were root mean square errors of $1.35^{\circ}$ in average and $3.63^{\circ}$ in yaw estimation.