• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.151-155
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbance and performance improvement with the on-line learning in the position control of excavator attachment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.449-450
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• 2015

This paper describes performance evaluation results of a new dynamic bandwidth allocation algorithm for an XG-PON (10-Gbps-capable passive optical network) system without using an explicit request. An ONU (optical network unit) does not send its request to an OLT (optical line termination). The OLT monitors the upstream bandwidth usage of the ONU to estimate the request of the ONU.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.3-5
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• 1993

This paper presents a identification techniques of coherent generators for dynamic equivalents using artificial neural networks. In the developed neural network, inputs are the power system parameters which have a property of coherency. Outputs of the neural network are coherency and error indices which are derived from density measure concept. The learning of developed neural network is carried out by means of error back-propagation algorithm. Identification of coherent generators are implemented by proposed grouping algorithm using coherency and error indices. The proposed method is confirmed by simulations for 39-bus New England system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.5-91
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• 2001

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes accord Eng to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems ...

• Journal of Industrial Technology
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• v.21 no.A
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• pp.241-249
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• 2001

The objective of this paper is to develop the optimal path algorithm for dynamic route guidance system in advanced traveler information system (ATIS). The travel time is forecasted in each path between network nodes. Floyd-Warshall algorithm is used to find the optimal route based on this forecasted travel time in dynamic traffic network. This algorithm is modified to apply the real traffic network that has left-turn restriction, U-turn, and P-turn. A big value is assigned to one of arcs in turn restriction and a virtual node is used to consider U-turn and P-turn for Floyd-Warshall algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.551-560
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• 1998

This paper presents a neural network model representing complex hydro-thermo-dynamic characteristics of a steam generator in nuclear power plants. The key modeling processes include training data gathering process, analysis of system dynamics and determining of the neural network structure, training process, and the final process for validation of the trained model. In this paper, we suggest a training data gathering method from an unstable steam generator so that the data sufficiently represent the dynamic characteristics of the plant over a wide operating range. In addition, we define the inputs and outputs of neural network model by analyzing the system dimension, relative degree, and inputs/outputs of the plant. Several types of neural networks are applied to the modeling and training process. The trained networks are verified by using a class of test data, and their performances are discussed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.81-94
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• 2012

This paper suggests PARED algorithm, a modified RED algorithm, that actively reacts to dynamic changes in network to apply packet drop probability flexibly. The main idea of PARED algorithm is that it compares the target queue length to the average queue length which is the criterion of changes in packet drop probability and feeds the gap into packet drop probability. That is, when the difference between the average queue length and the target queue length is great, it reflects as much as the difference in packet drop probability, and reflects little when the difference is little. By doing so, packet drop probability could be actively controled and effectively dealt with in the network traffic situation. To evaluate the performance of the suggested algorithm, we conducted simulations by changing network traffic into a dynamic stat. At the experiments, the suggested algorithm was compared to the existing RED one and then to ARED one that provided the basic idea for this algorithm. The results proved that the suggested PARED algorithm is superior to the existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1040-1045
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• 2002

This paper focuses on a hash-based, distributed Wet caching network that eliminates inter-cache communication. An agent program on cache servers, a mapping program on the DNS server, and other components comprised in a distributed Web caching network were modified and developed to implement a so-called "consistent" hashing. Also, a dynamic load balancing algorithm is proposed to address the load-balancing problem that is a key performance issue on distributed architectures. This algorithm effectively balances the load among cache servers by distributing the calculated amount of mapping items that have higher popularity than others. Therefore, this developed network can resolve the imbalanced load that is caused by a variable page popularity, a non-uniform distribution of a hash-based mapping, and a variation of cache servers.

• ETRI Journal
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• v.26 no.2
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• pp.185-188
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• 2004

In this paper, we design a two-step scheduling algorithm to support multiple bandwidth allocation policies for upstream channel access in an Ethernet passive optical network. The proposed scheduling algorithm allows us a simultaneous approach for multiple access control policies: static bandwidth allocation for guaranteed bandwidth service and dynamic bandwidth allocation for on-demand, dynamic traffic services. In order to reduce the scheduling complexity, we separate the process of the transmission start- time decision from the process of grant generation. This technique does not require the timing information of other bandwidth allocation modules, so respective modules are free from a heavy amount of timing information or complex processing.

• ETRI Journal
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• v.27 no.6
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• pp.802-805
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• 2005

A dynamic bandwidth allocation (DBA) scheme, an inter -optical network unit (ONU) bandwidth scheduling, is presented to provide quality of service (QoS) to different classes of packets in Ethernet passive optical networks (EPONs). This scheme, referred to as TADBA, is based on efficient threshold reporting from, and adaptive polling order rearranging of, ONUs. It has been shown that the network resources are efficiently allocated among the three traffic classes by guaranteeing the requested QoS, adaptively rearranging the polling orders, and avoiding nearly all fragmentation losses. Simulation results using an OPNET network simulator show that TADBA performs well in comparison to the available allocation scheme for the given parameters, such as packet delay and channel utilization.