• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.517-519
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• 2022

In 5G network environment, proactive mobility management is essential as 5G mobile networks provide new services with ultra-low latency through dense deployment of small cells. The importance of a system that actively controls device handover is emerging and it is essential to predict mobile trajectory during handover. Sequence-to-sequence model is a kind of deep learning model where it converts sequences from one domain to sequences in another domain, and mainly used in natural language processing. In this paper, we developed a system for predicting mobile trajectory in a wireless network environment using sequence-to-sequence model. Handover speed can be increased by utilize our sequence-to-sequence model in actual mobile network environment.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.53-61
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• 2014

For monitoring the flight trajectory and the status of a launch vehicle, the mission control system in NARO space center process data acquired from the ground tracking system, which consists of two tracking radars, four telemetry stations, and one electro-optical tracking system. Each tracking unit exhibits its own tracking error mainly due to multi-path, clutter and radio refraction, and by utilizing only one among transmitted informations, it is not possible to determine the actual vehicle trajectory. This paper presents a way of generating flight trajectory via post-processing the data received from the ground tracking system. The post-processing algorithm is divided into two parts: compensation for atmosphere radio refraction and multi-sensor fusion, for which a decentralized Kalman filter was adopted and implemented based on constant acceleration model. Applications of the present scheme to real data resulted in the flight trajectory where the tracking errors were minimized than done by any one sensor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.7
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• pp.76-82
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• 2004

A method of designing a state feedback gam achieving a specified insensitivity of the closed-loop trajectory by the singularly perturbed unified system using the operators is proposed. The order of system is reduced by the singular perturbation technique by ignoring the fast mode in it. The proposed method takes care of the actual trajectory variations over the range of the singular perturbation parameter. Necessary conditions for optimality are also derived. The previous study was done in the continuous time system The present paper extends the previous study to the discrete system and the ${\delta}-operating$ system that unifies the continuous and discrete systems. Advantages of the proposed method are shown in the numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1557-1560
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• 1997

In this paper, we have built an experimental magnetic levitation system for a possible use of control education. We have give a mathermatical model of the nonlinear system and have shown the stability region of the linearized system when it is controlled by a PD controller. We also proposed a neural network control system which uses a neural network as a feedforward controller thgether with a conventional feedback PF controller. We have generated a desired output trajectory, which was designed for the benefit of the generalization of the neural network controller, and trained the desired output trajectory, which was desigend for the benefit of the generalization of the neural netowrk controller, and trained a neural network controller with the data of the actual input and the output of the system obtained by applying the desired output trajectroy. A good tracking performance was observed for both the desired trajectiories used and not used for the neural network training.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.40-43
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• 1996

An off-line programming, OLP, system is widely used in automation fines. To help an on-line robot system to carry out desirable tasks planned by the off-line simulation, an approach to the real-time communication is presented. The OLP system developed consists of a software, a host computer(PC), a SCARA robot body, four servo drivers, and four independent joint controllers. This study focuses on the software where real-time communication is included. The software, can be used in teaching, trajectory planning, real-time running, and performance evaluation. The evaluation of different control algorithms is one of the merits of the software. The software can give servo commands for task running. A comparison of generated and corresponding actual trajectories provides the evaluation of task performance. The safety, of the OLP system is ensured by alarming malfuntions of the system. The OLP system developed can reduce the teaching time and increase the user's convenience.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.427-432
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• 2018

This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1853-1858
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• 2004

This paper presents the development of a full order sliding mode controller for tracking problem of a class of uncertain dynamical system, in particular, the direct drive robot manipulators. By treating the arm as an uncertain system represented by its nominal and bounded parametric uncertainties, a new robust fullorder sliding mode tracking controller is derived such that the actual trajectory tracks the desired trajectory as closely as possible despite the non-linearities and input couplings present in the system. A proportional-integral sliding surface is chosen to ensure the stability of overall dynamics during the entire period i.e. the reaching phase and the sliding phase. Application to a three DOF direct drive robot manipulator is considered.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.150-154
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• 2022

The Automatic Ship Identification System(AIS) is importantly used to evaluate the trajectory of ships and the possibility of collision between ships. However, it is difficult to provide real-time information due to the limitation of the transmission intervals. Most of the studies to improve this are conducted based on ideal data, so there is a problem that it is hard to respond to the actual situation. Therefore, in this paper, we propose a discrete Kalman filter-based method that reflects the turning angle according to the type of trajectory, to provide real-time position information on real-time data. In addition, the accuracy evaluation of the proposed algorithm is conducted through experiments using actual data.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.217-222
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• 2021

EOTS(Electro-Optical Tracking System) is utilized in acquiring visual information to assess a guided missile's performance. As the missile travels so fast, it is almost impossible for operator to re-capture the lost target. The RADAR or telemetry data are used to re-capture the lost target however facilities to receive real time data is required, which constrains selection of tracking site. Unlike aforementioned data, pre-calculated nominal trajectory can be used without communication facility. This paper proposes a method to predict lost target's state by employing nominal trajectory. Firstly, observed trajectory and nominal trajectory are compared using DTW and current target's state is predicted. The predicted state is used as observation in Kalman filter's correction phase to predict target's next state. The plausibility of the proposed method is verified by applying on actual missile trajectory.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1431-1438
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• 2013

A pack-level battery hardware-in-the-loop simulation (B-HILS) platform is implemented. It consists of dynamic vehicle models using PSAT and multiple control interfaces including real-time 3D driving and GPS mode. In real-time 3D driving mode, user can drive a virtual vehicle using actual drive equipment such as steering wheel and accelerator to generate the cycle profile of the battery. In GPS mode, actual road traffic and terrain effects can be simulated using GPS data while the trajectory is displayed on Google map. In the latter part of the paper, several performance tests of an actual lithium-polymer battery pack are carried out utilizing the developed system. All experiments are conducted as parts of actual development process of a commercial battery pack adopting 2nd generation Prius as a target vehicle model. Through the experiments, the low temperature performance and fuel efficiency of the battery are quantitatively investigated in comparison with the original nickel-metal hydride (NiMH) pack of the Prius.