• Title/Summary/Keyword: fuzzy-random variable

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Study of the Constant Current Fuzzy Control System Design using CRS Algorithm during Inverter DC Resistance Spot Welding Process (인버터 DC 저항점용접 공정에서 CRS 알고리즘을 이용한 정전류 퍼지 제어시스템 설계에 관한 연구)

  • Park, Hyoung-Jin;Park, Pyeong-Won;Yu, Ji-Young;Kim, Dong-Cheol;Kang, Mun-Jin;Rhee, Se-Hun
    • Journal of Welding and Joining
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    • v.28 no.6
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    • pp.76-83
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    • 2010
  • The purpose of this study is to propose a method to decide near-optimal settings of the constant current fuzzy control parameters using a controlled random search. This method tries to find the near-optimal settings of the constant current fuzzy control parameters through experiments. It has an advantage of being able to carry out searches in the search domain which includes some irregular points. The method suggested in this study was used to determine the fuzzy control parameters by which the desired welding current were formed during inverter DC resistance spot welding. The output variable was the ITAE (integral of time multiplied by the absolute error). This output variable was determined according to the input variables, which are the GE, GDE, and GDU. This study described how to obtained near-optimal welding current condition over a wide search space conducting a relatively small number of experiments.

Simulation of the Air Conditioning System Using Fuzzy Logic Control

  • Mongkolwongrojn, M.;Sarawit, W.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2270-2273
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    • 2003
  • Fuzzy logic control has been widely implemented in air conditioning and ventilation systems which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters , several fuzzy logic controllers had been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control room temperature and humidity in the precision air conditioning systems. The nonlinear mathematical model was formulated using energy and continuity equations. MATLAB was used to simulate the fuzzy logic control of the multi-variable air conditioning systems. The simulation results show that fuzzy logic controller can reduce the steady-state errors of the room temperature and relative humidity in multivariable air conditioning systems. The offset are less than 0.5 degree Celsius and 3 percent in relative humidity respectively under random step disturbance in heating load and moisture load respectively

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Event Based Tele-Operation with Variable Holding Time (가변 지속시간을 갖는 이벤트 기반 원격제어)

  • 박준영;박장현
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.12
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    • pp.70-77
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    • 2002
  • Necessity of the tole-operation has been increased in many fields. Since the Internet is inexpensive and available all over the world, it is a strong candidate for the transmission media of the tole-operation. However, the Internet has random time delays that may cause instability in the system especially if the tole -operation is bilateral. In the past few years many attempts have been made to overcome the random time delay, So far, they are still insufficient in terms of performance. The ‘Variable holding time’ is introduced to improve the performance of the ‘Event based tole-operation’ which controls a system with a non-time action reference. By holding each event for proper time, the system can quickly respond and be stabilized. The proper holding time should be selected based on the characteristics of the task that the system performs. The factors that reflect those characteristics are investigated. The fuzzy logic is employed to obtain the proper holding time for each event while the tole-operation system is in operation. The experimental results presented in this paper verify effectiveness of the proposed method.

The Evaluation of Failure Probability for Rock Slope Based on Fuzzy Set Theory and Monte Carlo Simulation (Fuzzy Set Theory와 Monte Carlo Simulation을 이용한 암반사면의 파괴확률 산정기법 연구)

  • Park, Hyuck-Jin
    • Journal of the Korean Geotechnical Society
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    • v.23 no.11
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    • pp.109-117
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    • 2007
  • Uncertainty is pervasive in rock slope stability analysis due to various reasons and subsequently it may cause serious rock slope failures. Therefore, the importance of uncertainty has been recognized and subsequently the probability theory has been used to quantify the uncertainty since 1980's. However, some uncertainties, due to incomplete information, cannot be handled satisfactorily in the probability theory and the fuzzy set theory is more appropriate for those uncertainties. In this study the random variable is considered as fuzzy number and the fuzzy set theory is employed in rock slope stability analysis. However, the previous fuzzy analysis employed the approximate method, which is first order second moment method and point estimate method. Since previous studies used only the representative values from membership function to evaluate the stability of rock slope, the approximated analysis results have been obtained in previous studies. Therefore, the Monte Carlo simulation technique is utilized to evaluate the probability of failure for rock slope in the current study. This overcomes the shortcomings of previous studies, which are employed vertex method. With Monte Carlo simulation technique, more complete analysis results can be secured in the proposed method. The proposed method has been applied to the practical example. According to the analysis results, the probabilities of failure obtained from the fuzzy Monte Carlo simulation coincide with the probabilities of failure from the probabilistic analysis.

PI and Fuzzy Logic Controller Based 3-Phase 4-Wire Shunt Active Filters for the Mitigation of Current Harmonics with the Id-Iq Control Strategy

  • Mikkili, Suresh;Panda, Anup Kumar
    • Journal of Power Electronics
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    • v.11 no.6
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    • pp.914-921
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    • 2011
  • Commencing with incandescent light bulbs, every load today creates harmonics. Unfortunately, these loads vary with respect to their amount of harmonic content and their response to problems caused by harmonics. The prevalent difficulties with harmonics are voltage and current waveform distortions. In addition, Electronic equipment like computers, battery chargers, electronic ballasts, variable frequency drives, and switching mode power supplies generate perilous amounts of harmonics. Issues related to harmonics are of a greater concern to engineers and building designers because they do more than just distort voltage waveforms, they can overheat the building wiring, cause nuisance tripping, overheat transformer units, and cause random end-user equipment failures. Thus power quality is becoming more and more serious with each passing day. As a result, active power filters (APFs) have gained a lot of attention due to their excellent harmonic compensation. However, the performance of the active filters seems to have contradictions with different control techniques. The main objective of this paper is to analyze shunt active filters with fuzzy and pi controllers. To carry out this analysis, active and reactive current methods ($i_d-i_q$) are considered. Extensive simulations were carried out. The simulations were performed under balance, unbalanced and non sinusoidal conditions. The results validate the dynamic behavior of fuzzy logic controllers over PI controllers.

Artificial Intelligence Applications as a Modern Trend to Achieve Organizational Innovation in Jordanian Commercial Banks

  • Al-HAWAMDEH, Majd Mohammed;AlSHAER, Sawsan A.
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.3
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    • pp.257-263
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    • 2022
  • The objective of this study was to see how artificial intelligence applications affected organizational innovation in Jordanian commercial banks. Both independent and dependent variables were measured in three dimensions: expert systems, neural network systems, and fuzzy logic systems for artificial intelligence applications variable. Product innovation, process innovation, and management innovation for the organizational innovation variable. To achieve study objectives, a questionnaire was developed and distributed to a sample of one hundred fifty-three managers in Jordanian commercial banks, who were selected according to the simple random sampling method. Except for the neural network systems dimension, which comes in at an average level, the study indicated that there is a high level of organizational innovation and artificial intelligence applications. Furthermore, the findings revealed that artificial intelligence applications have a significant impact on organizational innovation in Jordanian commercial banks, with the most important artificial intelligence application being a fuzzy logic system. The study suggested keeping track of technological advancements in the field of artificial intelligence applications and incorporating them into banking operations by benchmarking with the best commercial bank practices and allocating a portion of the budget to technological applications and infrastructure development, as well as balancing between technology use and information security risks to ensure client privacy is protected.

Semi-Active Control of a Suspension System with a MR Damper of a Large-sized Bus (MR 댐퍼를 이용한 대형 버스 현가장치의 반능동 제어)

  • Yoon, Ho-Sang;Moon, Il-Dong;Kim, Jae-Won;Oh, Chae-Youn;Lee, Hyung-Won
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.21 no.4
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    • pp.683-690
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    • 2012
  • In this work, the semi-active control of a large-sized bus suspension system with an MR damper was studied. An MR damper model that can aptly describe the hysteretic characteristics of an MR damper was adopted. Parameter values of the MR damper model were suitably modified by considering the maximum damping force of a passive damper used in the suspension system of a real large-sized bus. In addition, a fuzzy logic controller was developed for semi-active control of a suspension system with an MR damper. The vertical acceleration at the attachment point of the MR damper and the relative velocity between sprung and unsprung masses were used as input variables, while voltage was used as the output variable. Straight-ahead driving simulations were performed on a road with a random road profile and on a flat road with a bump. In straight-ahead driving simulations, the vertical acceleration and pitch angle were measured to compare the riding performance of a suspension system with a passive damper with that of a suspension with an MR damper. In addition, a single lane change simulation was performed. In the simulation, the lateral acceleration and roll angle were measured in order to compare the handling performance of a suspension system using a passive damper with that of a suspension system using an MR damper.

The concept of σ-morphism as a probability measure on the set of effects (이펙트 집합에서 확률측도로서 시그마 모르피즘 개념)

  • Yun, Yong-Sik;Kang, Kyoung-Hun;Park, Jin-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.3
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    • pp.371-374
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    • 2009
  • In this paper, we introduce the concepts of effects and observable as generalizations of event and random variable, respectively. Also, we introduce the concept of $\sigma$-morphism and we investigate some results on $\sigma$-morphism as a probability measure on the set of effects.

Implementing an Adaptive Neuro-Fuzzy Model for Emotion Prediction Based on Heart Rate Variability(HRV) (심박변이도를 이용한 적응적 뉴로 퍼지 감정예측 모형에 관한 연구)

  • Park, Sung Soo;Lee, Kun Chang
    • Journal of Digital Convergence
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    • v.17 no.1
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    • pp.239-247
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    • 2019
  • An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.