• IE interfaces
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• v.19 no.1
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• pp.34-42
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• 2006

This paper presents a scheme for a hierarchical production scheduling and control system for a refrigerator factory with mixed model assembly lines. The setting of the factory is as follows. There are three mixed-model assembly lines called main line A, B and C and two batch lines that supply parts to the main lines. For each of the main lines, three work-centers are dedicated to them. The sub-lines and work-centers produce parts in batch type. An incoming production order from the master planner is characterized by its product type, amount, and due date. Under this situation, the proposed scheme has several features to schedule and control the above mentioned factory; 1) select the starting time and the place (assembly line) for an order processing, 2) devise a way to control orders to be processed as scheduled, and 3) reschedule orders when something unexpected happen. Finally, this paper provides a case study where the proposed scheme is applied to.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.499-505
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• 1998

In developing an automated surface inspect algorithm, we have designed a hierarchical classifier using neural network. The defects which exist on the surface of cold mill strip have a scattering or singular distribution. We have considered three major problems, that is preprocessing, feature extraction and defect classification. In preprocessing, Top-hit transform, adaptive thresholding, thinning and noise rejection are used Especially, Top-hit transform using local minimax operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, and histogram ratio features are calculated. The histogram ratio feature is taken from the gray-level image. For defect classification, we suggest a hierarchical structure of which nodes are multilayer neural network classifiers. The proposed algorithm reduced error rate by comparing to one-stage structure.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1002-1010
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• 2005

We study on the implementation of reconfigurable position control system which is based on Open Control Platform(OCP) for Unmanned Expedition Vehicles(UEV) in ubiquitous environment. The control system uses hierarchical control structure and OCP structure which contains three layers such as core OCP, reconfigurable control API(Application Programmer Interface), generic hybrid control API. The goal of our research is to implement an UEV control system using advanced software technology. As a specific control problem, we study a transition management problem between PID control and neural network control depending on fault or parameter change of the plant, i.e., UEV. The concept of the OCP-based software-enabled control can provide synergy effect by the integration of software component, middleware, network communication, and control, and thus can be applied to various systems in ubiquitous environment.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.192-200
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• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.207-210
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• 1997

In this paper, a hierarchical fuzzy controller for stabilization of the inverted pendulum system is proposed. The facility of this hierarchical fuzzy controller which has a swing-up control mode and a stabilization one, moves a pendulum in an initial natural stable equilibrium point and a cart in arbitrary position to an unstable equilibrium point and a center of rail. Specially, the virtual equilibrium point (.PHI.$_{VEq}$ ) which describes functionally considers the interactive dynamics between a position of cart and a angle of inverted pendulum is introduced. And comparing with the convention optimal controller, the proposed hierarchical fuzzy inference made substantially the inverted pendulum system robust and stable.e.

• Journal of Ocean Engineering and Technology
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• v.15 no.4
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• pp.108-114
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• 2001

Petri nets have been introduced as a powerful analyzing and design tool for the discrete systems such as sequential control systems. However, one of the important problems in its applications is that the model can be analyzed hardly when we deal with large scale systems because of increase of the number of Petri net components. To overcome this problem, some methods for dividing or reducing of Petri net have been suggested. In this paper, an approach for hierarchical expression of Petri net based on Sequential function Chart(SFC) and Bottom Up oriented Mehodology(BUM) is proposed. Especially, some definitions and rules are defined in order to divide and compose sub Petri nets. A measuring tank system will be described as a typical kind of discrete systems and modeled by some sub Petri nets based on the SFC and BUM by the proposed method in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3468-3495
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• 2015

In this paper, we present a multi-chain based hierarchical topology control algorithm (MCHTC) for wireless sensor networks. In this algorithm, the topology control process using static clustering is divided into sensing layer that is composed by sensor nodes and multi-hop data forwarding layer that is composed by leader nodes. The communication cost and residual energy of nodes are considered to organize nodes into a chain in each cluster, and leader nodes form a tree topology. Leader nodes are elected based on the residual energy and distance between themselves and the base station. Analysis and simulation results show that MCHTC outperforms LEACH, PEGASIS and IEEPB in terms of network lifetime, energy consumption and network energy balance.

• Journal of Digital Contents Society
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• v.7 no.1
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• pp.35-40
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• 2006

Game AI(Artificial Intelligence) technologies implement the movement of autonomous characters and control the movement of Non-Player Characters(NPC). In this paper, we present several types of game AI control systems such as Movement Scripts, FSM(Finite State Machines), Hierarchical State Machines, fuzzy State Machines, and Pathfinding techniques and their limitations.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.05a
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• pp.26-31
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• 2001

Petri nets(PN) have been introduced as a poweful analyzing and design tool for the discrete systems such as sequential control systems. However, one of the important problems in its applications is that the model can not be analyzed easily when we deal with large scale systems because of increase of the number of components of the systems. To overcome this problem, some methods for dividing or reducing of PN have been suggested. In this paper, an approach for hierarchical expression of PN based on Sequential Function Chart(SFC) and Bottom Up oriented Mehodology(BUM) is proposed. Especially, some definition and rules are defined in order to divide and compose sub PN. A measuring tank system will be described as a typical kind of discrete systems and modeled by some sub PN based on the SFC and BUM by the proposed method in this paper.

• Journal of Environmental Science International
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• v.4 no.1
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• pp.71-80
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• 1995

A discrete state space model for a multiple-reach river system is formulated using the dynamics of biochemical oxygen demand(BOD) and dissolved oxygen(DO). A hierarchical optimization technique, which is applicable to large-scale systems with time-delays in states, is also described to control stream quality in a river as an optimal manner based on the interaction prediction method. The steady state tracking error of the proposed method is determined analytically and a necessary and sufficient condition on which a constant target tracking problem has zero steady-state error is derived. Computer simulations for the river pollution model illustrate the algorithm.