• Journal of IKEEE
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• v.27 no.4
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• pp.430-438
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• 2023

The Modular Multilevel Converter (MMC) has emerged as a key component in HVDC systems due to its ability to efficiently transmit large amounts of power over long distances. In such systems, accurate estimation of the MMC capacitor voltage is of utmost importance for ensuring optimal system performance, stability, and reliability. Traditional methods for voltage estimation may face limitations in accuracy and robustness, prompting the need for innovative approaches. In this paper, we propose a novel distributed neural network observer specifically designed for MMC capacitor voltage estimation. Our observer harnesses the power of a multi-layer neural network architecture, which enables the observer to learn and adapt to the complex dynamics of the MMC system. By utilizing a distributed approach, we deploy multiple observers, each with its own set of neural network layers, to collectively estimate the capacitor voltage. This distributed configuration enhances the accuracy and robustness of the voltage estimation process. A crucial aspect of our observer's performance lies in the meticulous initialization of random weights within the neural network. This initialization process ensures that the observer starts with a solid foundation for efficient learning and accurate voltage estimation. The observer iteratively updates its weights based on the observed voltage and current values, continuously improving its estimation accuracy over time. The validity of proposed algorithm is verified by the result of estimated voltage at each observer in capacitor of MMC.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.25-36
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• 1996

We have analyzed the reliability of failure models In grid topology circuit switched networks. These models are grid topology circuit_ switched networks. and each node transmits packets to object node using flooding search routing method. We hypothesized that the failure of each link Is Independent. We have analyzed for the performance estimation of failure models It using joint probability method to the reliability of a small grid topology circuit switched network. and compared analytic output with simulated output. Also. We have evaluated the reliability of networks using call blocking Probability occurred in circuit switched networks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.101-108
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• 2005

In this paper, the design problem of local area networks is defined as finding the network topology minimizing cost subject to reliability constraint. The design problem includes issues such as multiple choices of link type for each possible link, multiple choices of hub type for each hub, and allocation of the users to the hubs. To efficiently solve the problem, a genetic approach is suggested. According to the experiments, the proposed approach improves search performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1700-1707
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• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.762-766
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• 1998

Mechanical valve is one of the most widely used implantable artificial organs, Since its failure (mechanical failures and thrombosis to name two representative example) means the death of patient, its reliability is very important and early noninvasive detection is essential requirement . This paper will explain the method to detect the thrombosis formation by spectral analysis and neural network. In order quantitatively to distinguish peak of a normal valve from that of a thrombotic valve, a 3 layer backpropagation neural network, which contains 7,000 input nodes, 20 hidden layer and 1output , was employed. The trained neural network can distinguish normal and thrombotic valve with a probability that is higher than 90% . In conclusion, the acoustical spectrum analysis coupled with a neural network algorithm lent itself to the noninvasive monitoring of implanted mechanical valves. This method will be applied to be applied to the performance evaluation of other implantable rtificial organs.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.49-57
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• 2017

IoT can be connected through a single network not only objects which can be connected to existing internet but also objects which has communication capability. This IoT environment will be a huge change to the existing communication paradigm. However, the big security problem must be solved in order to develop further IoT. Security mechanisms reflecting these characteristics should be applied because devices participating in the IoT have low processing ability and low power. In addition, devices which perform abnormal behaviors between objects should be also detected. Therefore, in this paper, we proposed D-IDS technique for efficient detection of malicious attack nodes between devices participating in the IoT. The proposed technique performs the central detection and distribution detection to improve the performance of attack detection. The central detection monitors the entire network traffic at the boundary router using SVM technique and detects abnormal behavior. And the distribution detection combines RSSI value and reliability of node and detects Sybil attack node. The performance of attack detection against malicious nodes is improved through the attack detection process. The superiority of the proposed technique can be verified by experiments.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2259-2268
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• 1997

Multistage interconnection networks(MINs) provide a high-bandwidth communication between processors and/or memory modules in a cost-effective way. In this paper, we propose a class of multipath MINs, called the Augmented Modified Delta(AMD) network, and analyze its performance and reliability. The salient features of the AMD network include fault-tolerant capability, modular structure, and high performance, which are essential for real-time parallel/distributed processing environments. The class of the AMD network retains well-known characteristics of the Kappa network, but it's design procedure is more systematic. Like Delta networks, all the AMD networks are topologically equivalent with each other.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.328-330
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• 2001

무선 인터넷 환경하에서 신뢰성이 보장되어야 할 데이터의 전송이나 음성 데이터의 전송시에 혼잡으로 인한 손실이 발생했을 때, 라우터나 스위치에서의 손실을 네트웍 레이어에서 직접 복구를 함으로서 양단에서의 손실을 극소화함은 물론 지연시간을 최소화하여, 멀티미디어 데이터의 재생시에 치명적으로 작용할 수 있는 Jitter의 발생을 줄이며 네트웍 레이어에서의 손실을 최소화함으로써 무선 링크를 통한 복구 횟수를 줄여서 신뢰성 향상 및 전반적인 모바일 네트웍의 성능을 향상시킬 수 있는 방법을 제시하고 이에 대한 시뮬레이션을 통해 그 성능을 입증하도록 하겠다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.7-13
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• 2012

This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.

• Convergence Security Journal
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• v.19 no.3
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• pp.13-19
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• 2019

MANET has many security vulnerabilities because it consists of only mobile nodes using wireless. In particular, it is a very important factor determining network performance that excludes the participation of malicious nodes through accurate reliability measurements and authentication of nodes participating in the network. In this paper, we proposed a technique applied with blockchain technology in order to prevent forgery of authentication information for nodes participating in the network. And, an area-based hierarchical structure was applied to increase the efficiency of authentication for nodes and apply the optimal technique of block generation and exchange protocol. In addition, four data payloads were added to the block header in order to add authentication information for nodes in block. To improve the reliability by applying the blockchain technique to the hop-by-hop data transfer method between mobile nodes, blockchain exchange protocol through transaction creation, block packaging and verification processes were implemented. We performed the comparative experiment with the existing methods to evaluate the performance of the proposed method and confirmed the excellent performance by the experiment results.