• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.733-739
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• 2011

Recently, a lots of research proposals and results on mobile sensor network are actively announced. The most of such works are based on general-purposed network simulators such as ns-2, mathlab, etc. But, It is not easy to model and simulate the detail activities of each sensor node, data deliveries between them, and its cost such as power consumption and resource utilization, so that the simulation results of those simulators show the limited aspects of overall networks features or performance metrics. In this paper proposed, power consumption of each node, performance, mobility, and location information in operation-level of the network that can simulate a wireless sensor network simulator platform. Because the network routing algorithm analysis of being developed in an existing becomes available, the proposed simulator can usability in the new network routing algorithm development.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.23-31
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• 2010

This paper suggests a multiple robot simulator which considers the uncertainties in robot motion and sensing. A mobile robot moves with errors due to some kinds of uncertainties from actuators, wheels, electrical components, environments. In addition, sensors attached to a mobile robot can't make accurate output information because of uncertainties of the sensor itself and environment. Uncertainties in robot motion and sensing leads researchers find difficulty in building mobile robot navigation algorithms. Generally, a robot algorithm without considering unexpected uncertainties fails to control its action in a real working environment and it leads to some troubles and damages. Thus, the authors propose a simulator model which includes robot motion and sensing uncertainties to help making robust algorithms. Sensor uncertainties are applied in range sensors which are widely used in mobile robot localization, obstacle detection, and map building. The paper shows performances of the proposed simulator by comparing it with a simulator without any uncertainty.

• Journal of Power Electronics
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• v.11 no.4
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• pp.424-429
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• 2011

In this paper, the simulator of an on-line monitoring system for the range extender electric vehicle has been developed. The messages from the four control modules, the air pressure and fuel level sensors data, and the on/off switching states of 31 indicator lamps can be received through the control area network (CAN), and displayed on the graphic panel. The simulator was designed using the four DSP boards, variable resistors, and toggle switches instead of the four control modules, sensors, and switching state of indicator lamps on an actual series hybrid electric vehicle (SHEV) bus, respectively. The performance of the monitoring technologies was verified with the simulator at the laboratory, and then it was tested on an actual SHEV bus. The simulator is very useful at the initial development of the monitoring system at the hybrid-type or electrical vehicles.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.917-922
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• 2016

There are many researches related on the brain wave signals to monitor the state of human health. Especially, some patients in the medical hospital need to be monitored in case of emergencies such as a seizure, an epilepsy and so on. To support QoS of the brain wave network in the hospital is a vital issue and the Opnet simulator is used for this experiment. So the efficient network topology is required for the stability of the brain wave network service. The brain waves of the patients are collected from the sensor devices in the network. Two different sensor network topologies are suggested and simulated for the comparison of the network performance. One topology is localized and the other is non-localized network. The simulation is operated with the Opnet simulator.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.34-46
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• 2016

Networked Control System (NCS) has evolved in the past decade through the advances in communication technology. The problems involved in NCS are broadly classified into two categories namely network issues due to network and control performance due to system network. The network problems are related to bandwidth allocation, scheduling and network security, and the control problems deal with stability analysis and delay compensation. Various delays with variable length occur due to sharing a common network medium. Though most delays are very less and mostly neglected, the network induced delay is significant. It occurs when sensors, actuators, and controllers exchange data packet across the communication network. Networked induced delay arises from sensor to controller and controller to actuator. This paper presents an adaptive delay compensation process for efficient control. Though Smith predictor has been commonly used as dead time compensators, it is not adaptive to match with the stochastic behavior of network characteristics. Time delay adaptive compensation gives an effective control to solve dead time, and creates a virtual environment using the plant model and computed delay which is used to compensate the effect of delay. This approach is simulated using TrueTime simulator that is a Matlab Simulink based simulator facilitates co-simulation of controller task execution in real-time kernels, network transmissions and continuous plant dynamics for NCS. The simulation result is analyzed, and it is confirmed that this control provides good performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.4
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• pp.13-28
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• 2009

Routing protocols in Delay/Disruption Tolerant Networks(DTN) are important to enhance the performance of transmission delay and delivery success ratio. In this paper, we propose an efficient DTN routing algorithm, called "Nobility Pattern based Routing(MPR)", that controls the total number of transferred message copies based on mobility patterns of mobile nodes. We consider a realistic "Levy walk" mobility pattern that has a super-diffusive property which well represents human mobility pattern. We implemented a DTN simulator using ONE simulator for the proposed MPR algorithm and Levy walk mobility pattern. Simulation results show that mobility patterns are very important for accurate evaluation of DTN routing performance, and the proposed MPR enhances the routing performance of delivery delay and success delivery ratio under realistic mobility pattern.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.9-18
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• 2020

The development of a large-scale thermal power plant control simulator consists of water/steam systems, air/combustion systems, pulverizer systems and turbine/generator systems. Modeling is possible for all systems except mechanical turbines/generators. Currently, there have been attempts to develop neural network simulators for some systems of a boiler, but the development of simulator for the whole system has never been completed. In particular, autoTuning, one of the key technology developments of all power generation companies, is a technology that can be achieved only when modeling for all systems with high accuracy is completed. The simulation results show accuracy of 95 to 99% or more of the actual boiler system, so if the field PID controller is fitted to this simulator, it will be available for fault diagnosis or auto-tuning.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.10
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• pp.67-76
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• 1993

This paper presents the design and implementation of SVSIM (Sogang VHDL SIMulator), a multi-level VHDL simulator, designed for the construction of an integrated VGDL design environment. The internal model of SVSIM is the hierarchical C/DFG which is extended from C/DFG to include the network hierarchy and local/glabal control informations. Hierarchical network is not flattened for simulation, resulting in the reduction of space complexity. The predufined/user-defined types except for the record type and the predefined/user-defined attributes are supported in SVSIM. Algorithmic-level descriptions can be siumlated by the support of recursive procedure/function calls. Input stimuli can be generated by command script in stimuli file or in VHDL source code. Experimential results show SVSIM can be efficiently used for the simulation of the pure behavioral descriptions, structural descriptions or mixture of these.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.2-129
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• 2001

Visual effects are important cues for providing occupant s with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant´s posture, therefore, the total body motion must be considered in a graphic simulator. A real time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and acceleration. A multibody system analysis software, MADYMO, was used in the motion analysis of an adult male dummy in the seated position. Position data of the head were collected as inputs to the viewpoint movement. Based on these data, a back- propagation neural network was ...

• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.55-68
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• 2005

The advancement in semiconductor technology is leading toward smaller critical dimension designs and larger wafer manufactures. Due to such phenomena, semiconductor industry is in need of an accurate control of the process. Photolithography is one of the key processes where the pattern of each layer is formed. In this process, precise superposition of the current layer to the previous layer is critical. Therefore overlay parameters of the semiconductor photolithography process is targeted for this research. The complex relationship among the input parameters and the output metrologies is difficult to understand and harder yet to model. Because of the superiority in modeling multi-nonlinear relationships, neural networks is used for the simulator modeling. For training the neural networks, conjugate gradient method is employed. An experiment is performed to evaluate the performance among the proposed neural network simulator, stepwise regression model, and the currently practiced prediction model from the test site.