• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.214-220
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• 2021

In this study, we constructed several scenarios that are required for LED lighting, and we designed and implemented an LED lighting control system to operate these scenarios to confirm their behavior. An LED lighting control system is a hybrid control board that is designed by combining LED controllers and SMPS, consisting of an AC/DC power supply part that converts AC 220 V into DC 12 V, and a drive and control part that controls the scenario and color of the LED module. Conventional LED light controllers have an input power of DC 12 V, so when using the input AC 220 V, the SMPS must be connected to the LED light controller. To eliminate this inconvenience, a hybrid LED lighting control system was configured to combine LED lighting controllers and SMPS into one control system. Furthermore, we designed a control system to represent the most appropriate color according to the input of the distance and illumination using a fuzzy control system to conduct computer simulations.

• Nonlinear Functional Analysis and Applications
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• v.26 no.4
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• pp.717-731
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• 2021

In this paper, we introduce and study a new class of random generalized nonlinear implicit variational-like inclusion with random fuzzy mappings in a real separable Hilbert space and give its fixed point formulation. Using the fixed point formulation and the proximal mapping technique for strongly maximal monotone mapping, we suggest and analyze a random iterative scheme for finding the approximate solution of this class of inclusion. Further, we prove the existence of solution and discuss the convergence analysis of iterative scheme of this class of inclusion. Our results in this paper improve and generalize several known results in the literature.

• Nonlinear Functional Analysis and Applications
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• v.27 no.4
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• pp.881-894
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• 2022

In this paper, we consider a class of random generalized nonlinear mixed variational inclusions with random fuzzy mappings and random relaxed cocoercive mappings in real Hilbert spaces. We suggest and analyze an iterative algorithm for finding the approximate solution of this class of inclusions. Further, we discuss the convergence analysis of the iterative algorithm under some appropriate conditions. Our results can be viewed as a refinement and improvement of some known results in the literature.

• Journal of the Korea Convergence Society
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• v.4 no.3
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• pp.35-41
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• 2013

Grouping problem with similarities between DNA sequences are studied. The similaritymeasure and the distance measure showed the complementary characteristics. Distance measure can be obtained by complementing similarity measure, and vice versa. Similarity measure is derived and proved. Usefulness of the proposed similarity measure is applied to grouping problem of 25 cockroach DNA sequences. By calculation of DNA similarity, 25 cockroaches are clustered by four groups, and the results are compared with the previous neighbor-joining method.

• Journal of the Korean Society of Industry Convergence
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• v.10 no.4
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• pp.271-274
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• 2007

In this paper, we propose a intelligent controller design method for the water level control of the power plant drum in the form of nonminimum phase system. The proposed method is based on T. Takagi and M. Sugeno's fuzzy model. And we illustrate the improved characteristics as the simulation results, comparing with the conventional the PID and LQ controller design method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.197-200
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• 2000

최대 수용전력 시계열 데이터를 수집하여 카오스적 성질을 분석하고 퍼지 제어기로부터 추론되어진 제어 값으로 특정 플랜트의 단기예측을 수행하는 카오스 퍼지 제어기를 구성하고 시뮬레이션을 통하여 실제 데이터와의 오차 검토를 통하여 카오스 퍼지 제어기의 강인성을 검증하고 이 시스템을 통하여 얻어진 결과와 실제 데이터를 비교함으로써 제어기의 성능을 평가한다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.213-216
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• 2000

퍼지제어기를 실제 플랜트에 적용할 경우, 모델링 오차와 플랜트에 대한 관련지식의 부족으로 만족할 만한 제어 결과를 기대하지 못한다. 이러한 경우 제어기 성능을 향상시키기 위해 제어인자를 다시 조정해야 하고, 이 조정과정은 시행착오방법으로 수행되기 때문에 많은 시간과 비용을 필요로 한다. 본 논문에서는 퍼지 논리를 사용하여 스케일링 계수를 자동조정하는 퍼지 레귤레이터를 제안하였다. 스케일 계수의 출력 범위와 오차, 오차 변화량 따라 퍼지 레귤레이터는 적절한 스케일링 계수값을 결정함으로써 퍼지제어기의 성능을 향상시키게 된다. 제안한 방법의 타당성을 확인하기 위해 2차 플랜트에 적용하여 모의실험을 수행하였다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.93-96
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• 2000

본 논문에서는 신경망제어기의 출력을 보상하는 퍼지보상기를 갖는 신경망제어기에 관하여 제안하였다. 학습이 완료된 신경망제어기를 사용하더라도 예상치 못한 외란으로 인해 플랜트의 출력이 좋지 못한 경우가 있는데, 이것을 적절하게 조절해 주기 위해 퍼지보상기를 사용하여 원하는 결과를 얻을 수 있도록 하였다. 그리고, 플랜트의 동적 특성을 계속해서 학습할 수 있도록 시간이 경과함에 따라 신경망제어기의 성능이 향상되도록 하였다. 이것을 확인하기 위해서, 2차 플랜트에 적용하여 제안한 제어기의 성능을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.5
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• pp.1-12
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• 2000

In this paper we propose a design method of the adaptive fuzzy controller for autonomous navigation of mobile robots based on the fuzzy theory. We present two improvements. First, unnecessary rules in the fuzzy inference process make data processing time increase. We reduce this data processing time by generating suitable fuzzy inference rules and membership functions according to the current state of a mobile robot. It is implemented with the clustering method using input and output data pairs, and then it is possible for a mobile robot to navigate in shorter processing time with less fuzzy inference rules. Second, existing algorithms used fixed membership functions of input and output variables, hence converged slowly. We improve convergence time via scaling membership functions generated by the clustering method. To evaluate and compare the performance of the proposed method with the existing fuzzy navigation controller, computer simulations and navigation experiments of a mobile robot are Presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.391-398
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• 2009

In this study, we introduce the design methodology of an optimized fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. The displacement change the position of ball leads to the change of the angle of the beam which determines the position angle of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. We introduce the fuzzy cascade controller scheme which consists of the outer(1st) controller and the inner(2nd) controller as two cascaded fuzzy controllers, and auto-tune the control parameters(scaling factors) of each fuzzy controller using HFCGA. The inner controller controls the position of lever arm which corresponds to the position angle of a servo motor and the outer controller decides the set-point value of the inner controller. HFCGA is a kind of parallel genetic algorithms(PGAs), and helps alleviate the premature convergence being generated in conventional genetic algorithms (GAs). For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.