• Journal of the Korean Mathematical Society
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• v.42 no.5
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• pp.1071-1086
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• 2005

In this paper, we introduce a discrete time to the model to describe the time between infection of a CD4$^{+}$ T-cells, and the emission of viral particles on a cellular level. We study the effect of the time delay on the stability of the endemically infected equilibrium, criteria are given to ensure that the infected equilibrium is asymptotically stable for all delay. We also obtain the condition for existence of an orbitally asymptotically stable periodic solution.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.29-39
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• 1997

A discrete model reference control scheme for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of discrete time nonlinar dynamics. The schmen employs a neural network to identify the plan systems, wher the neural network estimates the nonlinear dynamics of the plant. The algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed. Whith thd resulting identification model which contains the neural networks, the parameters of controller are adjusted. The proposed scheme is applied to the vehicle active four wheel system and shows the validity and effectiveness through simulation. The three-degree-of freedom vehicle handling model is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the yaw rate overshoot reduction of a typical mid-size car is improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response andl smaller side slip angle than the 2WS case.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.47-56
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• 2003

Geometric cutting-simulation and verification play an important role in detecting NC machining errors in mold & die manufacturing and thereby reducing correcting time & cost on the shop floor. Current researches in the area may be categorized into view-based, solid-based, and discrete vector-based methods mainly depending on workpiece models. Each methodology has its own strengths and weaknesses in terms of computing speed, representation accuracy, and its ability of numerical inspection. The paper proposes a hybrid modeling scheme for workpiece representation with z-map model and discrete vector model, which performs 3-axis and 5-axis cutting-simulation via tool swept surface construction by connecting a sequence of silhouette curves.

• Proceedings of the Korea Society for Simulation Conference
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• 1996.05a
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• pp.15-15
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• 1996

A shop floor control system (SFCS) is the central part of a CIM system used to control the activities of several pieces of manufacturing equipment (e.g., NC machines, robots, conveyors, AGVs, AS/RS). The SFCS receives orders and related process plans, and then performs selecting a specific process routing, allocating resources, scheduling the workpieces, downloading the processing instructions (e.g., RS-274 instructions for NC machines, VAL II programs for robot), monitoring the progress of activities, detecting and recovering from errors, and preparing reports on the status of the manufacturing system. Simulation has been utilized in discovering control policies used for resolving shop floor be control problems such as resource contentions, part dispatching, deadlock. The simulation model must be designed to respond to real-time data coming from a shop floor. However, to rapidly build a realtime simulation model of SFCS cannot be easily accomplished. This talk is to address an automatic program generator of discrete event simulation model for shop floor control from process plans and resource models. The program generator is capable of constructing complete discrete simulation models for multi-product and multi-stage flexible manufacturing systems.

• Wind and Structures
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• v.20 no.2
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• pp.169-189
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• 2015

To investigate the effects of "sudden change" of wind fluctuations on vehicle running performance, which is caused by the artificial discrete simulation of wind field, a three-dimensional vehicle model is set up with multi-body dynamics theory and the vehicle dynamic responses in crosswind conditions are obtained in time domain. Based on Hilbert Huang Transform, the effects of simulation separations on time-frequency characteristics of wind field are discussed. In addition, the probability density distribution of "sudden change" of wind fluctuations is displayed, addressing the effects of simulation separation, mean wind speed and vehicle speed on the "sudden change" of wind fluctuations. The "sudden change" of vehicle dynamic responses, which is due to the discontinuity of wind fluctuations on moving vehicle, is also analyzed. With Principal Component Analysis, the comprehensive evaluation of vehicle running performance in crosswind conditions at different simulation separations of wind field is investigated. The results demonstrate that the artificial discrete simulation of wind field often causes "sudden change" in the wind fluctuations and the corresponding vehicle dynamic responses are noticeably affected. It provides a theoretical foundation for the choice of a suitable simulation separation of wind field in engineering application.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.303-306
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• 1996

We propose a robust tuning method of the quadratic criterion based iterative learning control(Q-ILC) algorithm for discrete-time linear batch system. First, we establish the frequency domain representation for batch systems. Next, a robust convergence condition is derived in the frequency domain. Based on this condition, we propose to optimize the weighting matrices such that the upper bound of the robustness measure is minimized. Through numerical simulation, it is shown that the designed learning filter restores robustness under significant model uncertainty.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.590-592
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• 1997

A Discrete Event Dynamic System is a system whose states change in response to the occurrence of events from a predefined event set. A major difficulty in developing analytical results for the systems is the lack of appropriate modeling techniques. This paper proposes the use of Real-time Temporal Logic as a modeling tool for the analysis and control of DEDS. The Real-time Temporal Logic Frameworks is extended with a suitable structure of modeling hard real-time constraints. Modeling rules are developed for several specific situations. It is shown how the graphical model can be translated to a system of linear equations and constraints.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.613-626
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• 2011

In this paper, we focus on the pinwheel task model with a variable voltage processor with d discrete voltage/speed levels. We propose an intra-task DVS algorithm, which constructs a minimum energy schedule for k tasks in O(d+k log k) time We also give an inter-task DVS algorithm with O(d+n log n) time, where n denotes the number of jobs. Previous approaches solve this problem by generating a canonical schedule beforehand and adjusting the tasks' speed in O(dn log n) or O($n^3$) time. However, the length of a canonical schedule depends on the hyper period of those task periods and is of exponential length in general. In our approach, the tasks with arbitrary periods are first transformed into harmonic periods and then profile their key features. Afterward, an optimal discrete voltage schedule can be computed directly from those features.

• Journal of Sensor Science and Technology
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• v.28 no.4
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• pp.216-220
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• 2019

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.