• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.28-30
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• 1998

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.267-273
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• 2007

This paper presents the implementation of an educational kit for intelligent system control education. Neural network control algorithms are presented and control hardware is embedded to control the inverted pendulum system. The RBF network and the MLP network are implemented and embedded on the DSP 2812 chip and other necessary functions are embedded on an FPGA chip. Experimental studies are conducted to compare performances of two neural control methods. The intelligent control educational kit(ICEK) is implemented with the inverted pendulum system whose movements of the cart is limited by space. Experimental results show that the neural controllers can manage to control both the angle and the position of the inverted pendulum systems within a limited distance. Performances of the RCT and the FEL control method are compared as well.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.553-559
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• 1998

Simple Genetic Algorithm(SGA) proposed by J. H. Holland is a population-based optimization method based on the principle of the Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. Although GA goes well in many applications as an optimization method, still it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, specially, since there is no deterministic solution, a heuristic trial-and error procedure is usually used to determine the systems' parameters. As an alternative scheme, therefore, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve. In this paper we review the existing co-evolutionary algorithms and propose co-evolutionary schemes designing intelligent systems according to the relation between the system's components.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.31-35
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• 1998

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.109-116
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• 2005

Proposed in this paper is an intelligent management system for evaluating science research projects based on fuzzy neural networks with genetic algorithms. This system was planned, designed and tested employing theories and approaches of software engineering. This system was then applied to evaluate science research projects of the Natural Science Foundation of Guangdong Province, People’s Republic of China. The outcome / results shows the feasibility and validity of the system and its possible application to other intelligent management systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.361-363
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• 2007

Using intelligent systems, many users do effectively their works. In general, the effective usages of the systems have to possess the usability and accuracy. So, we need some measurements for evaluating the performance of the criteria. But, in most cases, objective measurements for the evaluation are not. In this paper, we propose a measurement technique for objective evaluated measuring of intelligent systems using probability measure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.93-104
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• 2005

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.714-719
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• 2005

In this paper, the informative space is proposed to implant ubiquitous functions into physical spaces. We merge physical and virtual spaces through the space structurization using an RFID system, and solve the space localization and mapping problem for a robot to navigate through the distribution and synthesis of information and knowledge. To distribute knowledge flexibly and reliably to changing environment and also to develop a system which allows a robot to invoke and merge the distributed knowledge more freely, we employ a novel approach of knowledge management based on Web services. The proposed method is verified by building a physical space with two kinds of RFID tags and a virtual space with knowledge database based on Web services.

• Smart Structures and Systems
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• v.1 no.1
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• pp.1-12
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• 2005

This paper describes the area of intelligent systems research as funded by the Civil and Mechanical Systems (CMS) Division of the National Science Foundation (NSF). With developments in computer science, information technology, sensing and control the design of typical machines and structures by civil and mechanical engineers is evolving toward intelligent systems that can sense, decide and act. This trend toward electro-mechanical design is well-established in modern machines (e.g. vehicles, robots, disk drives) and often referred to as mechatronics. More recently intelligent systems design is becoming an important aspect of structures, such as buildings and bridges. We briefly review recent developments in structural control, including the role that NSF has played in their development, and discuss on-going CMS activities in this area. In particular, we highlight the interdisciplinary initiative on Sensors and Sensor Networks and the Network for Earthquake Engineering Simulation (NEES). NEES is a distributed cyberinfrastructure to support earthquake engineering research, and provides the pioneering NEES grid computing environment for simulation, teleoperation, data collection and archiving, etc.