• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.209-217
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• 2001

In this paper, we propose a linear quadratic regulator(LQR) controller design for the active suspension using evolution strategy(ES) and neural network. We can improve the inherent suspension problem, the trade-off between ride quality and suspension travel by selecting appropriate weight in the LQR-objective function. Since any definite rules for selecting weights do not exist, we replace the designers trial-and-error method with ES that is an optimization algorithm. Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle. The relationship between the frequencies and proper control gains are generalized by use of the neural networks. When the vehicle is driven, the trained neural network is activated and provides the proper gains for operating frequencies. And we adopted double sky-hook control to protect car component when passing large bump. Effectiveness of our design has been shown compared to the conventional sky-hook controller through simulation studies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.302-309
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• 2005

We have studied a model and application that evolves the behavioral knowledge of a virtual robot. The knowledge is represented in classification rules and a neural network, and is learned by a genetic algorithm. The model consists of a virtual robot with behavior knowledge, an environment that it moves in, and an evolution performer that includes a genetic algorithm. We have also applied our model to an environment where the robots gather food into a nest. When comparing our model with the conventional method on various test cases, our model showed superior overall learning.

• Geomechanics and Engineering
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• v.22 no.2
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• pp.133-142
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• 2020

The evolution of the mining-induced fracture network formed during longwall top coal caving (LTCC) has a great influence on the gas drainage, roof control, top coal recovery ratio and engineering safety of aquifers. To reveal the evolution of the mining-induced stress and fracture network formed during LTCC, the fracture network in front of the working face was observed by borehole video experiments. A discrete element model was established by the universal discrete element code (UDEC) to explore the local stress distribution. The regression relationship between the fractal dimension of the fracture network and mining stress was established. The results revealed the following: (1) The mining disturbance had the most severe impact on the borehole depth range between approximately 10 m and 25 m. (2) The distribution of fractures was related to the lithology and its integrity. The coal seam was mainly microfractures, which formed a complex fracture network. The hard rock stratum was mainly included longitudinal cracks and separated fissures. (3) Through a numerical simulation, the stress distribution in front of the mining face and the development of the fracturing of the overlying rock were obtained. There was a quadratic relationship between the fractal dimension of the fractures and the mining stress. The results obtained herein will provide a reference for engineering projects under similar geological conditions.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.21-42
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• 2015

This paper shows the case of the evolution of Korean e-Government services in the theoretical lens of Actor-Network Theory and Structuration Theory. It presents how human actors (i.e. presidents and the central administrations) and non-human actors (i.e. law, standards, and relay systems) have established as the one network together, and how this network affects the evolution of Korean e-Government services. This case demonstrates in public sector can adopt not only Actor-Network Theory, but also Structuration Theory to explain both micro and macro contexts. The practical implications are given especially for the developing countries in pursuing the rapid development process of e-Government services.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.111.3-111
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• 2002

$\textbullet$introduction $\textbullet$CO-evolution Algorithm $\textbullet$Subsumption Architecture $\textbullet$Neural Network $\textbullet$Khepera Robot

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.585-592
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• 1996

This paper analyzes the impact of digitalization on networks in Seoul Metropolitan Area by considering facility investment together with operatinng costs. A stepwise evolution method toward a digitalized double-homming architecture is proposed to accommodate most efficiently with existing analog-oriented networks.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.1-13
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• 2020

Recently, network infrastructure has evolved into a BizTech agile autonomous network to cope with the dynamic changes in the service environment. This survey presents the expectations from two different perspectives of the harmonization of network and artificial intelligence (AI) technologies. First, the paper focuses on the possibilities of AI technology for the autonomous network industry. Subsequently, it discusses how networks can play a role in the evolution of distributed AI technologies.

• Journal of Communications and Networks
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• v.4 no.4
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• pp.336-343
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• 2002

A major challenge for next generation mobile communication is capturing the system architecture’s complexity with all its internal and external dependencies. Seamless integration of heterogeneous environments in all system parts is a key requirement. Moreover, future systems have to consider the different evolution cycles of individual system parts. Among those, services are expected to change the fastest. With respect to these considerations, we propose an overall architecture for next generation mobile communication systems. It covers all system parts from wireless transmission to applications including network and middleware platform. Our approach focuses on adaptability in terms of recon- figurability and programmability to support unanticipated system evolution. Therefore, we consider abstraction layers which consist of adaptable cooperating components grouped by open platforms rather than rigid system layers. In addition to that, we introduce cross-layer cooperation allowing an efficient use of the available resources. Specific scenarios illustrate the feasibility of our approach.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.93-96
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• 2003

In this paper, we analyze the concept of network convergence and characteristics of Broadband convergence Network(BcN) from the service perspective where convergence would appear. We suggest the evolutionary 3 stage steps of BcN as an ideal network strategy when considering present network situation. We also propose the features of several representative services that are expected to emerge out of network convergence.