• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.136-138
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• 2006

Recently, network systems are widely used in several areas, and some considerable attentions have been directed to the Networked Control System(NCS). In NCS, network-induced delays are inevitable, and they sometimes degrade the performance of networked control systems to be a source of potential instability. In this paper, We proposes a compensation method for networked control system subject to network-induced delays by using a simple method, which is based on a sort of predictive strategy. To evaluate its feasibility and effectiveness, a real-time NCS for a rotary inverted pendulum is implemented via an Ethernet. Based on the experimental results. we show that the proposed simple method can be a practical and feasible solution to NCS design.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.290-290
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• 2010

For real-time recognition of accurate measuring instrument, the adaptive parameter typed Circular Nural-Net Recognition is proposed. The fast nural network system acted by a replacement of the conventional nural network has good real-time convergence. we are applied proposed nural network to utilize various control and investigation equipments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.133.5-133
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• 2001

The real-time industrial network, often referred to as fieldbus, is an important element for building automated manufacturing systems. Thus, in order to satisfy the real time requirements of field devices such as sensors, actuators, and controllers, numerous standard organizations and vendors have developed various fieldbus protocols. As a result, IEC 61158 protocol including Profibus, WorldFIP, and Foundation Fieldbus is recently announced as an international standard. Many fieldbus protocols have an important advantage over the widely used protocols such as Ethernet (IEEE 802.3) in terms of the deterministic characteristics of the fieldbuses. However, the application of fieldbus has been limited due to the high cost of hardware and the difficulty in interfacing with multi-vendor products. In order to solve these problems, computer network ...

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.255-260
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• 2001

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. 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. The TMS320C31 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.1-12
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• 2008

Home network is a technology that provides possibilities of monitoring/controling/mutilating-recognition between optional home network machines in residences. Currently, home network or other networks like entertainment, residential electronic networks are jumbled together with heterogeneous networks in a rampaging condition. In a reality of high expectation for home networks system like the mutual application for various machines, we are required to have the unification technology for conveniences to satisfy expectations. This thesis reflects how to develop Java applications or mutual products based on convenient interfaces actually that process various sensors which create real time data stream in Java platform through Java based sensor data-stream processing embedded middleware design and realization in real time.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.52.3-52
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• 2001

There are some problems to implement a realtime network system with Ethernet because the MAC(Medium Access Control) of Ethernet uses a CSMA/CD protocol, which introduces unexpected delays. In this paper, we designed a method to solve problems due to the Ethernet MAC. This method introduces a pseudo-MAC in application layer to support the real-time feature. So the presented method doesn´t need any modifications of protocols such as UDP/IP/MAC. The presented pseudo-MAC is based on both a token passing protocol and a publisher-subscriber protocol. The suggested realtime protocol is implemented and tested practically in a local area network. The proposed real-time network consists of a token controller node and general nodes.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.1-8
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• 2022

Supporting real-time flows with delay and throughput constraints is an important challenge for future wireless networks. In this paper, we develop an optimal scheduling scheme to optimally choose the packets to transmit. The optimal transmission strategy is based on an observable Markov decision process. The novelty of the work focuses on a priority-based probabilistic packet scheduling strategy for efficient packet transmission. This helps in providing guaranteed services to real time traffic in Heterogeneous Wireless Networks. The proposed scheduling mechanism is able to optimize the desired performance. The proposed scheduler improves the overall end-to-end delay, decreases the packet loss ratio, and reduces blocking probability even in the case of congested network.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.149-152
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• 2023

In this paper, I present an approach to implement a real-time video transceiver using software-defined radio (SDR). Through this, it is expected that it will be able to lower the access threshold and provide new perspectives and insights to researchers who want to study the recently spotlighted Open Radio Access Network (O-RAN) and implement it through SDR devices and open software.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.61-71
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• 2024

The dynamic nature of Online Social Networks (OSNs), especially on platforms like Twitter, presents challenges in identifying and responding to community attacks, particularly within Arabic content. The proposed integrated system addresses these challenges by achieving 91% accuracy in detecting real-time community event attacks while efficiently managing computational costs. This is accomplished through the use of specialized integrated approach clustering to detect both major and minor attacks. Additionally, the system leverages clustering algorithms, temporal modules, and social network graphs to identify events, map communities, and analyze online dynamics. An extensive parameter sensitivity analysis was conducted to fine-tune the algorithm, and the system's effectiveness was validated using a benchmark dataset, demonstrating substantial improvements in event detection.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.338-343
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• 1999

In this paper, the fuzzy neural network for the obstacle avoidance, which consists of the straight-line navigation and the barrier elusion navigation, is proposed and examined. For the straight-line navigation, the fuzzy neural network gets two inputs, angle and distance between the line and the mobile robot, and produces one output, steering velocity of the mobile robot. For the barrier elusion navigation, four ultrasonic sensors measure the distance between the barrier and the mobile robot and provide the distance information to the network. Then the network outputs the steering velocity to navigate along the obstacle boundary. Training of the proposed fuzzy neural network is executed in a given environment in real-time. The weights adjusting uses the back-propagation of the gradient of error to be minimized. Computer simulations are carried out to examine the efficiency of the real time learning and the guiding ability of the proposed fuzzy neural network. It has been shown that the mobile robot that employs the proposed fuzzy neural network navigates more safely with and less trembling locus compared with the previous reported efforts.