• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.557-565
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• 2018

For GNSS navigation in urban environment, a novel short delay multipath mitigation algorithm is proposed in this paper. This algorithm detects which satellite's signal is the multipath signal by using the constraint that GNSS receiver is equipped in a ground vehicle, then estimate new position after separating the measurement of that satellite. A criterion for detecting and validating the multipath signal depends on the performance grade of the GNSS receiver and the dynamics of the vehicle. In order to evaluate the proposed algorithm, the real data had been collected at the multipath environment of 4 scenarios. By post-processing the real data with both of the multipath mitigation algorithm in the receiver and the proposed algorithm, it can be checked that the position errors were less than 5 meters except the case that the number of visible satellite is lower than 5.

• Journal of Drive and Control
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• v.11 no.3
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• pp.47-54
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• 2014

Clutches are an integral part of the automatic transmission for changing gears. Modern automatic transmissions make extensive use of wet multiple-disc clutches employing hydraulic actuation mechanism with electronic control. Although nowadays, highly advanced shifting algorithm implements the superior shift quality and transmission efficiency, its performance should be based on smooth, reliable engagement with a reasonably durable friction material as well as stable clutch piston dynamics. Particularly, clutch filling control is the crucial part of shifting process because only the open-loop control is available due to the lack of measurement. In this paper, the effect of clutch-fill control parameters on clutch piston dynamics is experimentally investigated by using clutch piston test equipment which enables the clutch piston to actuate similar to real shifting conditions. The experimental analysis results can be expected to be utilized for the calibration of proportional solenoid valve as reference current profile data in vehicle test.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.47-53
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• 2002

The hydraulic design optimization and performance analysis of mixed-flow pumps for waterjet marine vehicle propulsion has been carried out using mean streamline analysis and three-dimensional computational fluid dynamics (CFD) code. In the present study the conceptual design optimization has been formulated with a non-linear objective function to minimize the fluid dynamic losses and then the commercial CFD code was incorporated to allow for detailed flow dynamic phenomena in the pump system. New designed mixed-flow model pump has been tested in the laboratory. Predicted performance curves by the CFD code agree very well with experimental data for a newly designed mixed-flow pump over the normal operating conditions. The design and prediction methods presented herein can be used efficiently as a unified hydraulic design process of mixed-flow pumps for waterjet marine vehicle propulsion.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.881-885
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• 2002

This paper presents the performance and the algorithm of a 1/3-octave band spectrum control system. The system is developed to provide various spectrums in a high intensity acoustic chamber. The required spectrum, which usually comes from launch vehicle company, starts from 25Hz band and ends 10kHz band. Automatic spectrum control system is preferred since the system requires short settling time to guarantee the safety of test objects and to reduce the amount of operating gas. The developed system adapted a PCI data-acquisition/signal-generation board installed in a personal computer to implement whole control logic. The control software used three cascade digital Butterworth filters using software. The filers are designed following ANSI S1.11 standard to implement 1/3 octave band filter bank. The graphical user interface of the system guides the user to follow standard operation procedure. The averaged control spectrum showed less than 0.05 dB in every running 1/3-octave band.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.461-468
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1086-1092
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1533-1556
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• 2017

The concept of trust in vehicular ad hoc networks (VANETs) is usually utilized to assess the trustworthiness of the received data as well as that of the sending entities. The quality of safety applications in VANETs largely depends on the trustworthiness of exchanged data. In this paper, we propose a self-organized distributed trust computing framework (DTCF) for VANETs to compute the trustworthiness of each vehicle, in order to filter out malicious nodes and recognize fully trusted nodes. The proposed framework is solely based on the investigation of the direct experience among vehicles without using any recommendation system. A tier-based dissemination technique for data messages is used to filter out non authentic messages and corresponding events before even going farther away from the source of the event. Extensive simulations are conducted using Omnet++/Sumo in order to investigate the efficiency of our framework and the consistency of the computed trust metrics in both urban and highway environments. Despite the high dynamics in such networks, our proposed DTCF is capable of detecting more than 85% of fully trusted vehicles, and filtering out virtually all malicious entities. The resulting average delay to detect malicious vehicles and fraudulent data is showed to be less than 1 second, and the computed trust metrics are shown to be highly consistent throughout the network.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.327-337
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• 2002

This paper applies a recently developed on-line parameter identification (PID) technique to sets of real flight data and compares the results with those of a state-of-the-art off-line PID technique. The on-line PID technique takes Linear Regression from Fourier Transformed equations and the off-line PID is based on the traditional Maximum Likelihood method. Sets of flight data from the NASA F/A-18 High Alpha research Vehicle (HARV) circraft, which has been recorded from specifically designed maneuvers and used for our line parameter estimation, are used for this study. The emphasis is given on the accuracy and on-line measure of reliability of the estimates. The comparison is performed for both longitudinal and lateral-directional dynamics for maneuvers at angles of attack ranging u=20°through $\alpha$=40°. Results of the two estimation processes are also compared with baseline wind tunnel estimates whenever possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.688-693
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• 2016

This paper describes the parachute dynamics modeling and simulation results for the development of training simulator of a HALO (High Altitude Low Opening) parachute, which is currently in use for military purposes. The target parachute is a rectangular shaped parafoil and its dynamic model is derived based on the real geometry data as the 9-DOF nonlinear equations of dynamics. The simulation was conducted through the moment of inertia and its aerodynamic derivatives to reflect the real characteristics based on the MATLAB/Simulink. In particular, its modeling includes the typical characteristics of the added mass and moment of inertia, which is shown in the strong effects in Lighter-Than-Air(LTA) flight vehicle. The proposed dynamic modeling was evaluated through the simulation under the spiral turning flight conditions of the asymmetric control inputs and compared with the performance index in the target parachute manual.