• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.24-34
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• 1994

Scientific involvement in complex decision-making system, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced and their weighted value structure is ignorant, the systems are become more complex. This paper presents a fuzzy dependenced relation model and fuzzy measure model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation and fuzzy measure in fuzzy systems theory. For the application of the model, a numdrical example is quoted.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.2
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• pp.59-67
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• 2016

Recently, the increased complexity of systems has made systems engineering necessary. It is very useful for system designers to understand the whole context of the concerned system based on systems engineering. A system model can be used to describe the outcome of a system design. A system model describes the system from the viewpoint of the stakeholder's needs using the mutually exclusive and collectively exhaustive principle. A system model can be used to smoothly design a large and complicated system based on the systems engineering development process. Many companies and countries are attempting to apply model-based systems engineering, and the significance of the system model quality is increasing as system models are referenced during system development. In this paper, we propose a quality assessment method for ontology which is one of system models by focusing on the system development process. First, in this process, a system developer should explicitly show the relationship between viewpoints. Then, the system developer should select dependent rather than independent viewpoints. With dependent viewpoints, each viewpoint used to describe the system has some logical relationship. The set of viewpoints makes it possible to show, not only tangible and physical system parts, but also conceptual system parts. In this paper, we develop an ontological system model of a Japanese weather observation system. By comparing some ontological system models, we verify the effectiveness of explicitly describing the relationships between viewpoints and select dependent viewpoints.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.213-240
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• 2012

Safety critical systems, real time systems, and event-based systems have a complex set of events and their own interdependency, which makes them difficult to test ma Safety critic Safety critical systems, real time systems, and event-based systems have a complex set of events and their own interdependency, which makes them difficult to test manually. In order to cut down on costs, save time, and increase reliability, the model based testing approach is the best solution. Such an approach does not require applications or codes prior to generating test cases, so it leads to the early detection of faults, which helps in reducing the development time. Several model-based testing approaches have used different UML models but very few works have been reported to show the generation of test cases that use events. Test cases that use events are an apt choice for these types of systems. However, these works have considered events that happen at a user interface level in a system while other events that happen in a system are not considered. Such works have limited applications in testing the GUI of a system. In this paper, a novel model-based testing approach is presented using business events, state events, and control events that have been captured directly from requirement specifications. The proposed approach documents events in event templates and then builds an event-flow model and a fault model for a system. Test coverage criterion and an algorithm are designed using these models to generate event sequence based test scenarios and test cases. Unlike other event based approaches, our approach is able to detect the proposed faults in a system. A prototype tool is developed to automate and evaluate the applicability of the entire process. Results have shown that the proposed approach and supportive tool is able to successfully derive test scenarios and test cases from the requirement specifications of safety critical systems, real time systems, and event based systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.236-236
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• 2000

Control of Industrial processes is very difficult due to nonlinear dynamics, effect of disturbances and modeling errors. M.Morari proposed Internal Model Control(IMC) system that can be effectively applied to the systems with model uncertainties and time delays. The advantage of IMC systems is their robustness with respect to a model mismatch and disturbances. But it was difficult to apply for nonlinear systems. Adaptive Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to identify a nonlinear dynamical systems. In this paper, we propose new IMC design method using adaptive neuro-fuzzy inference system for nonlinear plant. Numerical simulation results show that proposed IMC design method has good performance than classical PID controller.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.254-262
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• 2008

In this paper, we propose an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for full dynamics of nonlinear flight systems. It is assumed that the model uncertainties such as structured and unstrutured uncertainties, and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate the model uncertainties of nonlinear flight systems, and an adaptive DSC technique is extended for the disturbance attenuation of nonlinear flight systems. All weights of SRWNNs are trained on-line by the smooth projection algorithm. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance nom external disturbances can be obtained. Finally, we present the simulation results for a nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

• KIEE International Transactions on Power Engineering
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• v.4A no.2
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• pp.91-99
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• 2004

This paper illustrates a tie line constrained equivalent assisting generator (TEA G) model considering forced outage rates of transmission systems for reliability evaluation of interconnected power systems. Interconnections between power systems can provide improved levels of reliability. It is expected that the TEAG model developed in this paper will prove useful in the solution to problems related to the effect of transmission system uncertainties in the reliability evaluation of interconnected power systems. The characteristics and concept of this TEAG considering transmission systems are described in detail by sample studies on a simple test system.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1049-1057
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• 2011

Today, most weapon systems operate as component systems of SoS(System of Systems) and they produce synergy effects in the battle field by interoperating. In addition, the acquisition issues on weapon systems have expanded into SoS context including sustainment analysis. Availability is the sustainment KPP(Key Performance Parameter) of weapon systems. In this paper, a simulation model is proposed to analyze the availability of SoS. The simulation model consists of 5 modules: Mission and Task, System, System RBD, Maintenance system and a simulation engine. Then it was implemented and applied to a SoS. As a result of the application, the simulation model could be applied for analyzing the availability of the SoS and provided information about critical tasks and risky component systems to complete the given mission of the SoS.

• Structural Engineering and Mechanics
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• v.30 no.5
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• pp.619-645
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• 2008

This study presents the efficiency of simulating structural systems using a method that combines a simplified component model (SCM) and rigorous component model (RCM). To achieve a realistic simulation of structural systems, a numerical model must be adequately capturing the detailed behaviors of real systems at various scales. However, capturing all details represented within an entire structural system by very fine meshes is practically impossible due to technological limitations on computational engineering. Therefore, this research develops an approach to simulate large-scale structural systems that combines a simplified global model with multiple detailed component models adjusted to various scales. Each correlated multi-scale simulation model is linked to others using a multi-level hierarchical modeling simulation method. Simulations are performed using nonlinear finite element analysis. The proposed method is applied in an analysis of a simple reinforced concrete structure and the Reuipu Elementary School (an existing structure), with analysis results then compared to actual onsite observations. The proposed method obtained results very close to onsite observations, indicating the efficiency of the proposed model in simulating structural system behavior.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.39-45
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• 2022

For national industrial development in the Fourth Industrial Revolution, it is necessary to provide researchers with appropriate job information. This can be achieved by interconnecting the National Science and Technology Standard Classification System used for management of research activity with the Korean Employment Classification of Occupations used for job information management. In the present study, an automatic linkage model of classification systems is introduced based on a pre-trained language model for interconnecting science and technology information with job information. We propose for the first time an automatic model for linkage of classification systems. Our model effectively maps similar classes between the National Science & Technology Standard Classification System and Korean Employment Classification of Occupations. Moreover, the model increases interconnection performance by considering hierarchical features of classification systems. Experimental results show that precision and recall of the proposed model are about 0.82 and 0.84, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1419-1422
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• 1997

This paper deals with the Appliation of robust fault detection problem in uncertain linear systems, having both model mismatch and noise. A robust fault detection method presented by Kwon et al.(1994) for SISO uncertain systems. Here we experimented this method to the diesel engine systems described by difference ARMA models. The model mismatch includes here linearization error as well as undermodeling. Comparisons are made with alternative fault detection method which do not account noise. The new method is shown to have good performance.