• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.249-252
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• 1996

Fuzzy logic has been successfully used for nonlinear control systems. However, when the plant is complex or expert knowledge is not available, it is difficult to construct the rule bases of fuzzy systems. In this paper, we propose a new method of how to construct automatically the rule bases using fuzzy neural network. Whereas the conventional methods need the training data representing input-output relationship, the proposed algorithm utilizes the gradient of the object function for the construction of fuzzy rules and the tuning of membership functions. Experimental results with the inverted pendulum show the superiority of the proposed method in comparison to the conventional fuzzy controller.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.87-95
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• 2012

Up to now, industrial cranes play important roles as the effective machines to carry heavy loads in the manufacturing premise, in the construction field and so on. And, a crane is widely used not only to daily work but also to carry heavy materials efficiently in a construction site for prevention of accident. However, the crane operation is highly complicated even for experts. In this paper, we developed the content of the crane mounted on the controller. This content overload conditions in the operating environment for the crane operator to warn, and the operation of equipment has the capability to limit automatically. The content for crane controller is to alert the operator overload and to limit the operation of equipment for stabilizing capabilities. The content of the flexible algorithm is based on stabilizing controllers, PLC (Programmable Logic Controller) to connect for using the equipment and electrical control systems to ensure the safety of workers and to improve the ability to work possible.

• Computers and Concrete
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• v.24 no.5
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• pp.437-444
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• 2019

PLC and its expansion module, electric ball valve and cooling pipe, electric heating steel plate and various components of the system, which is used to control test and process data. By automatically adjusting the opening of the valve, the system makes the top temperature and cooling speed develop along the ideal temperature diachronic curve. Moreover, the system enables the temperature difference between inside and surface of test block limited in a given range by automatically controlling the surface board heating. The method of physical simulation test by sandbox with built-in cooling water pipe and heating rod is adopted. On the premise of a given standard value, the operation of the system is checked under different working conditions. Further, an extension of this system is proposed, which enables its application to obtain some thermal parameters when cooperating with numerical simulation.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.164-171
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• 2005

The importance of the life cycle cost analysis(LCCA) for apartment housing remodeling projects has been fully recognized over the last decade. Accordingly theoretical models, guidelines, and supporting software systems were developed for the life cycle cost analysis of apartment housing remodeling systems. However, the level of consensus on LCCA results is still low due to the lack of reliable data on remodeling activities for safety diagnosis. in order to predict the reliability based LCCA of the given case, suggested the remodeling strategies level after reviewing other related materials. Apply the real information of the economic index. And based on such analytical measures, remodeling and operation cost and LCC in remodeling strategies level have been predicted; suggests the basic information about remodeling interventions level for the apartment housing. The LCC analysis models and the fuzzy logic based safety assessment presented in this study can greatly contribute to the value-oriented design alternative selection, estimation of the economic analysis, and the allocation of budget for apartm.

• Korean Journal of Construction Engineering and Management
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• v.11 no.2
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• pp.74-82
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• 2010

A government agency has been announced to increase 23,663 hundred million wons by cost of design change which occurred in the pre-construction and construction phase. As design change is a phenomenon to occur by means of a characteristic of the building design that standardization is difficult, even if it is said that a perfect design is done in design phase, design change is prevented, and it is going to decrease, and there is a limit. Because there are some causes in all of the construction project, it is change order of client, relative system, unfit design and field condition, etc. In this study, we are suggested logic and basic model of the decision making support process model that it should selecting the optimal alternative through complex and quantitative analyzed: that is cost, performance and constructability as respect Owner or CMr is executing project under the CM delivery system construction project which it occurred design change.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of the Korean Geotechnical Society
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• v.22 no.10
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• pp.111-120
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• 2006

In this research, numerical simulations by PFC considering discrete element method are conducted to predict experimental results of large triaxial compression test with rockfill material for dam construction. For generation of compacted assembly with specific grain size distribution and initial material porosity, the clump logic method and expansion of generated particles are adapted. To predict stress-stain behavior of large triaxial test, discrete particle modelling is applied with micro parameters which are chosen by calibration process. It is expected that distinct particle modelling method could be used as a useful tool to investigate micro and macro behavior associated with geotechnical problems and develop a numerical laboratory.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.585-588
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• 1997

This paper presents a construction method of logic-based switching control system which operates in widely changing environments. The logic-based switching controller is composed of a family of candidate controllers together with a supervisor. The system does not require any identification schemes of environments. Switching from one candidate controller to another is carried out based on monitoring the output of the system. The basic ideas of adaptation are as follows: (1)each candidate controller is prepared for each environment in advance; (2)the supervisor applies a sequence of speculative controls to a plant with candidate controllers just after the control has started and just after the change of the environment has been detected. It is important that each candidate controller can keep the system stable during a sequence of speculative controls, and the most appropriate candidate controller for the environment to which the system is exposed can be selected before the last speculative control is ended. An application to an antiskid braking system clarifies the effectiveness of the proposed method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.8
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• pp.627-635
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• 2012

This study aims at developing an artificial neural network(ANN)-based predictive and adaptive temperature control method to control the openings at internal and external skins, and heating systems used in a building with double skin envelope. Based on the predicted indoor temperature, the control logic determined opening conditions of air inlets and outlets, and the operation of the heating systems. The optimization process of the initial ANN model was conducted to determine the optimal structure and learning methods followed by the performance tests by the comparison with the actual data measured from the existing double skin envelope. The analysis proved the prediction accuracy and the adaptability of the ANN model in terms of Root Mean Square and Mean Square Errors. The analysis results implied that the proposed ANN-based temperature control logic had potentials to be applied for the temperature control in the double skin envelope buildings.