• ETRI Journal
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• 제5권2호
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• pp.17-28
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• 1983

This paper deals with the problem of optimally controlling traffic flows in urban transportation traffic networks. For this, a nonlinear discrete-time model of urban traffic network is first suggested in order to handle the phenomenon of traffic flows such as oversaturatedness and/or undersaturatedness. Then an optimal control problem is formulated and a hierarchical optimization technique is applied, which is based upon a prediction-type two-level method of Hirvonen and Hakkala.

• Journal of Korean Institute of Industrial Engineers
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• 제40권2호
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• pp.184-194
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• 2014

Numerous studies have been studied to provide an efficient solution for the Nurse Rostering Problem (NRP), most of which have suffered from its complexity arising from incorporating nurse's work shift and ability. The test-bed data for the NRP is released for the public Competition in 2010. This study suggests a new mixed integer programming for Nurse Rostering Problem and develops a hybrid approach, where a hierarchical decomposition and the corresponding optimization are combined. The computation experiment is performed to show that the suggested algorithms may give a better solution in various instances, compared to the one appeared in the literature.

• Journal of the Korea Society of Computer and Information
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• 제11권1호
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• pp.147-155
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• 2006

Hierarchical Prefix Delegation (HPD) protocol refers to a type of solution to problems inherent in non-optimal routing which occurs with Network Mobility (NEMO) basic solution. However, because HPD cannot improve the micro-mobility problems, problem surfaces each time Mobile Network Node (MNN) changes the attachment point; as happens also in a Mobile IPv6 (MIPv6) protocol in sending Binding Update (BU) messages to Home Agent (HA) / Correspondent Nodes(CNs). By applying Hierarchical Mobile IPv6 protocol concept to HPD, this study proposes an algorithm for effectively handling micro-mobility problems which occur with HPD in a nested NEMO environment. By sending BU only to nearby Mobility Anchor Point(MAP) during MNN location change within a MAP's domain, the proposed protocol will alleviate service disruption delays and signaling loads during the handover process, overcoming the limitations of HPD.

• Journal of Power Electronics
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• 제18권5호
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• pp.1595-1607
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• 2018

In this paper, a hierarchical control strategy is introduced to control a new three-port multidirectional DC-DC converter for integrating an energy storage system (ESS) to a bipolar DC microgrid (BPDCMG). The proposed converter provides a voltage-balancing function for the BPDCMG and adjusts the states of charge (SoC) of the ESS. Previous studies tend to balance the voltage of the BPDCMG buses with active sources or by transferring power from one bus to another. Furthermore, the batteries available in BPDCMGs were charged equally by both buses. However, this power sharing method does not guarantee efficient operation of the whole system. In order to achieve a higher efficiency and lower energy losses, a triple-layer hierarchical control strategy, including a primary droop controller, a secondary voltage restoration controller and a tertiary optimization controller are proposed. Thanks to the multi-functional operation of the proposed converter, its conversion stages are reduced. Furthermore, the efficiency and weight of the system are both improved. Therefore, this converter has a significant capability to be used in portable BPDCMGs such as electric DC ships. The converter modes are analyzed and small-signal models of the converter are extracted. Comprehensive simulation studies are carried out and a BPDCMG laboratory setup is implemented in order to validate the effectiveness of the proposed converter and its hierarchical control strategy. Simulation and experimental results show that using the proposed converter mitigates voltage imbalances. As a result, the system efficiency is improved by using the hierarchical optimal power flow control.

• The Journal of Korea Robotics Society
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• 제17권1호
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• pp.16-24
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• 2022

This paper presents a method that can reduce the computational cost of the hierarchical quadratic programming (HQP)-based robot controller. Hierarchical controllers can effectively manage articulated robots with many degrees of freedom (DoFs) to perform multiple tasks. The HQP-based controller is one of the generic hierarchical controllers that can provide a control solution guaranteeing strict task priority while handling numerous equality and inequality constraints. However, according to a large amount of computation, it can be a burden to use it for real-time control. Therefore, for practical use of the HQP, we propose a method to reduce the computational cost by decreasing the size of the decision variable. The computation time and control performance of the proposed method are evaluated by real robot experiments with a 15 DoFs dual-arm manipulator.

• Transactions of the Korean Society of Mechanical Engineers
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• 제18권8호
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• pp.2016-2025
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• 1994

A hierarchical planning strategy for dextrous manipulation of multifingered hands with soft finger contact model is proposed. Dextrous manipulation planning can be divided into a high-level stage which specifies the position/orientation trajectories of the fingertips on the object and a low-level stage which determines the contact forces and joint trajectories for the fingers. In the low-level stage, various nonlinear optimization problems are formulated according to the contact modes and integrated into a manipulation planning algorithm to find contact forces and joint velocities at each time step. Montana's contact equations are used for the high-level planning. Quasi-static simulation results are presented and illustrated by employing a three-fingered hand manipulating a sphere to demonstrate the validity of the proposed low-level planning strategy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.313-316
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• 2008

에어컨 시스템은 압축기(Compressor), 응축기(Condenser), 증발기(Evaporator)와 확장밸브(Expansion Valve)로 구성되며, 에어컨 시스템에서 과열도와 저압(증발기의 압력)은 시스템의 효율 증대 및 성능 개선과 안정성에 대하여 결정적인 영향을 미친다. 따라서, 과열도와 저압을 조절하기 위해, 각각의 압축기내의 인버터 주파수와 확장밸브의 개도 제어가 중요하며 선형과 비선형 시스템 모두에 대하여 견실한 성능을 나타내고, 외란에 대하여 강인한 성능을 보이는 퍼지 제어기를 설계한다. 본 논문에서는 과열도와 저압을 제어하기 위하여, 3대의 확장밸브와 1대의 압축기를 가진 에어컨 시스템에 대하여 다중 퍼지 제어기를 설계한다. 또한, 각 제어 플랜트에 대하여 최적의 퍼지 제어기를 설계하기 위하여 3가지 최적화 알고리즘을 사용한다. 즉, 직렬 유전자 알고리즘(Serial Genetic Algorithm; SGA)과 병렬 유전자 알고리즘인 계층적 공정 경쟁 유전자 알고리즘(Hierarchical Fair Competition Genetic Algorithm; HFCGA), 그리고 Particle Swarm Optimization(PSO)을 사용하여 다중 퍼지 제어기를 최적화하고 시뮬레이션의 결과를 비교한다.

• ETRI Journal
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• 제28권5호
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• pp.631-637
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• 2006

In this paper we study the optimization issues of ring networks employing novel parallel multi-granularity hierarchical optical add-drop multiplexers (OADMs). In particular, we attempt to minimize the number of control elements for the off-line case. We present an integer linear programming formulation to obtain the lower bound in optimization, and propose an efficient heuristic algorithm called global bandwidth resource assignment that is suitable for the design of large-scale OADM networks.

• ETRI Journal
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• 제41권6호
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• pp.782-796
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• 2019

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large-scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi-Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.

• Journal of Computing Science and Engineering
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• 제1권2호
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• pp.195-210
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• 2007

Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.