• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.46-51
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• 2001

For Fast Real-time Recognition of Nonlinear Error Data, a new Neural Network algorithm which recognized the map in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion, In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of map, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear map information is processed,

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.46-51
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• 2001

For Fast Real-time Recognition of Nonlinear Error Data, a new Neural Network algorithm which recognized the map in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of map, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear map information is processed.

• International Journal of Air-Conditioning and Refrigeration
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• v.14 no.3
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• pp.85-93
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• 2006

The present study has been conducted to simulate dynamics of a gas engine-driven heat pump (GHP) for the design of control algorithm. The dynamic model of a GHP was based on conservation laws of mass and energy. For the control of refrigerant pressures, actuators such as an engine throttle valve, outdoor fans, coolant three-way valves and liquid injection valves were controlled by P or PI algorithm. The simulation results were found to be realistic enough to be applied for the control algorithm design. The model could be applied to build a virtual real-time GHP system so that it interfaces with a real controller for the purpose of developing control algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.423-427
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• 2003

In this paper, it is to development of brake system with ABS function for aircraft. The test of brake system is required before applying on aircraft. The real-time dynamic simulator with 5-D.O.F. aircraft dynamic model is developed for braking performance test of ABS (Anti-skid Brake System) control h/w with anti-skid brake functions. The dynamic simulator is real-time interface system that is composed of dynamic simulation parts, master control parts, digital and analog in/out interface parts, and user interface parts. The 5-D.O.F. aircraft dynamic model is composed of a big contour and a little contour by simulation s/w. The big contour represents the interactions of forces in airframe, nose and main landing gear, and engines on the center of gravity. The little contour represents interactions of wheel, braking units, hydraulic units and a control unit. ABS control h/w unit with ABS control algorithm is also developed and is tested with simulator under the some conditions of gripping coefficient. We have known that ABS control h/w unit on wet or snowy runway as well as dry runway very well protects wheel skid.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.312-319
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• 2005

For real time dynamic simulation, two different subsystem synthesis methods with independent generalized coordinates have been developed and compared. In each formulation, the subsystem equations of motion are generated in terms of independent generalized coordinates. The first formulation is based on the relative Cartesian coordinates with respect to moving subsystem base body. The second formulation is based on the relative joint coordinates using recursive formulation. Computational efficiency of the formulations has been compared theoretically by the arithmetic operational counts. In order to verify real-time capability of the formulations, bump run simulations of a quarter car model with SLA suspension subsystem have been carried out to measure the actual CPU time.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.7
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• pp.294-301
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• 2002

A new dynamic scheduling algorithm is proposed for CAN-based real-time system in this paper. The proposed algorithm is extended from an existing EDS(Earliest Deadline Scheduling) approach having a solution to the priority inversion. Using the proposed algorithm, the available bandwidth of network media can be checked dynamically, and consequently arbitration delay causing the miss of deadline can be avoided. Also, non-real time messages can be processed with their bandwidth allocation. Full network utilization and real-time transmission feasibility can be achieved through the algorithm. To evaluate the performance of algorithm, two simulation tests are performed. The first one is transmission data measurement per minute for periodic messages and the second one is feasibility in the system with both periodic messages and non-real time message.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.125-134
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• 1994

In real-time database systems, transactions's commitment done before the given deadlines is more important than just getting the maximum throughput. Transactions missing the given deadlines are no longer meaningful in real-time applications. Therefore, there is a need for new transaction processing models to meet the given deadlines in real-time database applications, because moat conventional transaction models are not designed to meet deadlines. In this paper we propose a new transaction models which uses multiple versions of a data item. The model uses read-from graphs and dynamic reorder of transactions to meet deadlines. A read-from graph contains the past read semantics of read operations and support the model to decide which database operation to be taken. Then, we show simulation results comparing the proposed model with other transaction models such as two phase locking model and the optimistic concurrency control model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.681-687
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• 2003

Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces fur realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and the T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in a successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. The dynamic T-search, which is proposed in this paper, combines conventional T-search and the concept of the dynmaic-window search which uses reduced searching windows or sets of triangular surface polygons at each frame by taking advantage of the information regarding dynamic charactereistics of a simulated vehicle. Numerical tests show improvement of searching speeds by about 5% for randomly distributed triangles. For continuous search following a vehicle path, which occurs in actual vehicle simulation, the searching speed becomes 4 times faster.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.645-650
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• 2010

In this paper we present the Bimodal-tram simulator using the PXI embedded real-time controllers. The Bimodal-tram is developed in KRRI (Korea Railroad Research Institute). The vehicle can be automatically operated by navigation control system (NCS). For the automatic driving, the vehicle lanes will be marked with permanent magnets that are placed in the ground. The vehicle is controlled by NCS. NCS governs the manual mode and automatic mode driving. The simulator is designed by an identical conception with the real control condition. The dynamic motion of vehicle is simulated by the nonlinear dynamic model. The control computer calculates the control values. The signal interface is linked by CAN communication. The simulation is processed by real-time base. The test driver can see the graphic motion of vehicle and can operate the steering wheel, gas and brake pedal to control direction and velocity of vehicle during the simulation. At present, the simulator is only operated by manual mode. The automatic mode will be linked after the control algorithm is finished. We will use the simulator to develop the control algorithm in the automatic mode. This paper shows the simulator designed for Bimodal-tram using real-time based controller. The results of the test using the simulator are presented and discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.