• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.137-147
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• 2015

In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

• 한국전산유체공학회:학술대회논문집
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• 2002.05a
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• pp.41-46
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• 2002

Computational study has been undertaken to investigate the aerodynamic influence of side jet on a supersonic missile and to find a similarity condition between the flight condition and the wind tunnel testing. Tasks were peformed to validate the existing Raytheon test body with side jet, to simulate the flow inside the supersonic wind tunnel, and to compare the flow fields between the missile in free flight and that in the wind tunnel. Then sub-scale model of body-tail configuration was analyzed to estimate the influence of the side jet on the missile components. It is found that the influence of side jet is not as significant on the tail region as on the body surface and a simple algebraic formula for aerodynamic coefficients accounting for the side jet as a point force may be cautiously utilized in setting up control logic.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.69-78
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• 2011

In this study, an optimization method using multi-objective genetic algorithm(MOGA) has been proposed to develop a fuzzy control algorithm that can effectively control a smart tuned mass damper(TMD). A 76-story benchmark building subjected to wind load was selected as an example structure. The smart TMD consists of 100kN MR damper and the natural period of the smart TMD was tuned to the first mode natural period of the example structure. Damping force of MR damper is controlled to reduce the wind-induced responses of the example structure by a fuzzy logic controller. Two input variables of the fuzzy logic controller are the acceleration of 75th floor and the displacement of the smart TMD and the output variable is the command voltage sent to MR damper. Multi-objective genetic algorithm(NSGA-II) was used for optimization of the fuzzy logic controller and the acceleration of 75th story and the displacement of the smart TMD were used as objective function. After optimization, a series of fuzzy logic controllers which could appropriately reduce both wind responses of the building and smart TMD were obtained. Based on numerical results, it has been shown that the control performance of the smart TMD is much better than that of the passive TMD and it is even better than that of the sample active TMD in some cases.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.

• Advances in Computational Design
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• v.5 no.4
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• pp.445-465
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• 2020

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.978-1002
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• 2019

With the rapid development of the Internet of Things, the problem of privacy protection has been paid great attention. Recently, Nikooghadam et al. pointed out that Kumari et al.'s protocol can neither resist off-line guessing attack nor preserve user anonymity. Moreover, the authors also proposed an authentication supportive session initial protocol, claiming to resist various vulnerability attacks. Unfortunately, this paper proves that the authentication protocols of Kumari et al. and Nikooghadam et al. have neither the ability to preserve perfect forward secrecy nor the ability to resist key-compromise impersonation attack. In order to remedy such flaws in their protocols, we design a lightweight authentication protocol using elliptic curve cryptography. By way of informal security analysis, it is shown that the proposed protocol can both resist a variety of attacks and provide more security. Afterward, it is also proved that the protocol is resistant against active and passive attacks under Dolev-Yao model by means of Burrows-Abadi-Needham logic (BAN-Logic), and fulfills mutual authentication using Automated Validation of Internet Security Protocols and Applications (AVISPA) software. Subsequently, we compare the protocol with the related scheme in terms of computational complexity and security. The comparative analytics witness that the proposed protocol is more suitable for practical application scenarios.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1172-1174
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• 2002

An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.812-815
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• 1996

In this paper, we consider the optimal control problem based on Discrete Event Dynamic Systems(DEDS) in the Temporal Logic framework(TLF) which have studied for a convenient modeling technique. The TLF is enhanced with objective functions(event cost indices) and a measurement space is also defined. Our research goal is the design of the optimal controller for DEDSs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.25-33
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• 1997

A DEDS is a system whose states change in response to the occurence of events from a predefined event set. In this paper, we consider the optimal control and reasoning problem for Discrete Event Systems(DES) in the Temporal Logic Framework(TEL) which have been recnetly defined. The TLE is enhanced with objective functions(event cost indices) and a measurement space is alos deined. A sequence of event which drive the system form a give initial state to a given final state is generated by minimizing a cost functioin index. Our research goal is the reasoning of optimal trajectory and the design of the optimal controller for DESs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following ; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Transactions on Electrical and Electronic Materials
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• v.11 no.6
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• pp.243-248
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• 2010

The emergence of different and disparate materials together with the convergence of both the 'old' and 'emerging' technologies is paving the way for integration of heterogeneous technologies that are likely to extend the limitations of silicon technology beyond the roadmap envisaged for complementary metal-oxide semiconductor. Formulation of new information processing concepts based on novel aspects of nano-scale based materials is the catalyst for new nanoarchitectures driven by a different perspective in realization of novel logic devices. The memory technology has been the pace setter for silicon scaling and thus far has pave the way for new architectures. This paper provides an overview of the inevitability of heterogeneous integration of technologies that are in their infancy through initiatives of material physicists, computational chemists, and bioengineers and explores the options in the spectrum of novel non-volatile memory technologies considered as forerunner of new logic devices.