• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.27-30
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• 2001

A inventory management system of the manufacturing industry has a model of different kinds according to the objective and the situation. A inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can have an intelligent inventory management system for optimized decision-making of forecasting data with expert's opinion in fuzzy environment. This inventory management system used an intelligence agent and it could be adapted to asystemenvironmentchangeinorder.

• Smart Structures and Systems
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• v.25 no.4
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• pp.401-408
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• 2020

This paper deals with the problem of global stabilization for a class of nonlinear control systems. An effective approach is proposed for controlling the system interaction of structures through a combination of parallel distributed compensation (PDC) intelligent controllers and fuzzy observers. An efficient approximate inference algorithm using expectation propagation and a Bayesian additive model is developed which allows us to predict the total number of control systems, thereby contributing to a more adaptive trajectory for the closed-loop system and that of its corresponding model. The closed-loop fuzzy system can be made as close as desired, so that the behavior of the closed-loop system can be rigorously predicted by establishing that of the closed-loop fuzzy system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.358-364
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• 2007

Intelligent walking modeling of humanoid robot using learning based neuro-fuzzy system is presented in this paper. Walking pattern, trajectory of the zero moment point (ZMP) in a humanoid robot is used as an important criterion for the balance of the walking robots but its complex dynamics makes robot control difficult. In addition, it is difficult to generate stable and natural walking motion for a robot. To handle these difficulties and explain empirical laws of the humanoid robot, we are modeling practical humanoid robot using neuro-fuzzy system based on the two types of natural motions which are walking trajectories on a t1at floor and on an ascent. Learning based neuro-fuzzy system employed has good learning capability and computational performance. The results from neuro-fuzzy system are compared with previous approach.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.559-562
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• 2004

In this paper, a new dual-rate digital control technique for the Takagi-Sugeno (T-S) fuzzy system is suggested. The proposed method takes account of the stabilizablity of the discrete-time T-S fuzzy system at the fast-rate sampling points. Our main idea is to utilize the lifted control input. The proposed approach is to obtain the dual-rate discrete-time T-S fuzzy system by discretizing the overall dynamics of the T-S fuzzy system with the lifted control, and then to derive the sufficient conditions for the stabilization in the sense of the Lyapunov asymptotic stability for this system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.67-70
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• 2004

Semiconductor Wet Station has a very important place in semiconductor process. It is important that to discharge chemical with fit concentration and temperature using chemical supply system for clean process. The chemical supply system which is used currently is not only difficult to make a fit mixing rate of chemical which is need in clean' process, but also difficult to make fit concentration and temperature. Moreover, it has high stability but it is inefficient spatially because its volume is great. We propose In-line System to improve system with implement analysis of fluid and thermal transfer on chemical supply system and understand problem of system.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.748-753
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• 2005

When the maneuver occurs, the performance of the standard Kalman filter has been degraded because mismatches between the modeled target dynamics and the actual target dynamics. To solve this problem, the unknown acceleration is determined by using the fuzzy logic based on genetic algorithm(GA) method. This algorithm is the method to estimate the increment of acceleration by a fuzzy system using th relation between maneuver filler residual and non-maneuvering one. To optimize this system, a GA is utilized. And then, the modified filter is corrected by the new update equation method which is a fuzzy system using the relation between the filter residual and its variation. To shows the feasibility of the suggested method with only one filter, the computer simulations system are provided, this method is compared with multiple model method.

• The Journal of Information Systems
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• v.18 no.3
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• pp.211-229
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• 2009

Recently, trends of information technology development include offerings of service for personalization, intelligence, and convergence. The research suggested a new tour system that tourists can make their tour packages by applying Semantic Web technology. The system includes ontologies and inference rules for offering intelligent and personalized service. Our system called MYT (Make Your Tour-package) was successfully demonstrated by employing realistic scenarios. Current version of the MYT system needs manager's intervention to link and integrate automatically ontology subsystem and Web service. In further study, the MYT will be extended to the system including a component integrating automatically subsystems and a component capturing and processing context data from RFID/USN.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.651-657
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• 1998

In this study, an intelligent scheduling with hybrid architecture, which integrates expert system and neural network, is proposed. Neural network is trained with the data acquired from simulation model of FMC to obtain the knowledge about the relationship between the state of the FMC and its best dispatching rule. Expert system controls the scheduling of FMC by integrating the output of neural network, the states of FMS, and user input. By applying the hybrid system to a scheduling problem, the human knowledge on scheduling and the generation of non-logical knowledge by machine teaming, can be processed in one scheduler. The computer simulation shows that comparing with MST(Minimum Slack Time), there is a little increment in tardness, 5% growth in flow time. And at breakdown, tardness is not increased by expert system comparing with EDD(Earliest Due Date).

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.106-108
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• 1997

Many new office buildings are being built as intelligent buildings equipped with building automation(HA) systems, office automation(OA) systems, and telecommunication(TC) systems in order to provide pleasant building environment and the ease of maintenance and facility management. Building control systems which are employed in intelligent buildings require varieties of advanced control systems and network systems for efficient integrated management. Design and installation of these types of advanced building control systems take a lot of efforts and also they are costly. In order to design these systems, it is necessary for the designers to have the integrated simulator including proper network system simulation. In this paper, the integrated simulator that consist of HVAC system, lighting system, elevator system, parking system based on the network system is presented. For the development of integrated simulator, AHENA which is the general-purpose software tool for a simulation with reinforced GUI is used.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.884-889
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• 2000

This paper describes the design and implementation of PCOAMC(PC-based Open Architecture Machine Controller) to be flexible and independent from the vendor-oriented hardware and software structure. This openness approach is able to enhance an intelligence and integration of a manufacturing system. The development methodology of PcOAMC is an Object-Oriented approach, and all modules in PcOAMC are modelled using UML(Unified Modelling Language) that provides an easy understanding and modification. In order to demonstrate an applicability of PcOAMC, a simple test has been executed by using the Client-Server system consisting of two PcOAMCS and bus monitoring system. The good results have been obtained, so that the developed controller is expected to be embedded into IMS(Intelligent Manufacturing System) as a basic unit.