• The Journal of Information Technology
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• v.4 no.2
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• pp.117-127
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• 2001

A self-structured neural network algorithm that finds optimal fuzzy membership functions and nile base to fuzzy model is proposed and a fuzzy-neural network controller is designed to get more accurate position and velocity control of wheeled mobile robot. This procedure that is composed of three steps has its own unique process at each step. The elements of output term set are increased at first step and then the rule base Is varied according to increase of the elements. The adjusted controller is in competition with controller which doesn't include any increased elements. The adjusted controller will be removed if the control-law lost. Otherwise, the controller is replaced with the adjusted system. After finished regulation of output term set and rule base, searching for input membership functions is processed with constraints and fine tuning of output membership functions is done.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1336-1337
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• 2011

본 논문은 최근 이슈가 되고 있는 해양에너지 중 해류의 흐름을 이용한 조류발전 시스템에 관한 것으로 대학 실험실규모에서 조류발전 시스템의 성능 및 특성을 효율적으로 시험 평가할 수 있도록 구성된 모의실험 장치에 관한 것이다. 조류발전은 타 에너지원에 비해 발전의 제한조건과 단점이 거의 없으며 국내 자연환경에 적용하기에 적합한 많은 장점을 가지고 있다. 본 논문에서는 조류발전 시스템의 성능 및 특성을 시험할 수 있도록 Motor-Generator Set(M-G Set)을 구성하였고, 최대출력제어를 위해 사전에 PSIM을 이용하여 시뮬레이션을 수행하여 최대 출력제어 알고리즘을 검증하였다. 구축된 조류 발전 모의실험 장치는 해양의 기후, 시간 변화에 따른 조류 속도 변화를 효율적으로 모의할 수 있도록 전동기 속도 제어를 가능하도록 하였다. 조류발전 시스템에서는 와류등으로 인해 유속을 측정하기 힘들고, 오차가 발생할 가능성이 많다. 그래서 유속 정보 없이 최대출력제어가 가능한 알고리즘을 시뮬레이션하여 수행하였다. 본 연구는 향후 실시간 발전 사항을 모니터링 할 수 있도록 LabVIEW 기반 모니터링 시스템에서 최대 출력제어 시스템을 구축하기 위한 좋은 자료로 쓰일 것이라 판단된다.

• Proceedings of the KIPE Conference
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• 2014.11a
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• pp.21-22
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• 2014

본 논문은 5-레벨 NPC/H-브릿지 (Neutral Point Clamped/H-bridge) 인버터의 최적 제어 세트 (finite-control-set) 모델 예측 제어 (MPC: Model Predictive Control) 방법을 제안한다. NPC/H-브릿지 인버터의 출력 전류 제어 및 DC-link 커패시터 전압 균형을 유지하기 위해 출력 전류와 DC-link 커패시터 전압을 예측하고, 하나의 비용 함수 (cost function)을 통해 최적의 스위칭 상태를 출력한다. PSIM 시뮬레이션을 통해 제안된 제어 알고리즘의 검증하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.780-785
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• 2007

This paper proposes the decentralized dynamic output feedback controller for discrete-time nonlinear interconnected systems using Takagi-Sugeno (T-S) fuzzy model. Through T-S fuzzy model of each subsystem, the decentralized dynamic output feedback controller is designed. By the closed-loop subsystems with controller, it represents the linear matrix inequality (LMI) for stability of whole interconnected system. The value of control gain are obtained by LMI. An example is given to show the experimentally verification discussed throughout the paper.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.173-181
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• 2014

This paper addresses the problem of model matching control for a class of systems modeled as input/output asynchronous sequential machines. Based on the feedback control scheme, we design a corrective controller that compensates the behavior of the closed-loop system so as to match a reference model. Whereas the former studies use state observers and the output burst for designing a controller, the present research needs neither the observer nor the output burst in controller design. We define the 'output equivalent machine' of the considered machine to describe the existence condition and the construction algorithm for the proposed controller. A case study is provided to show the operation of the proposed corrective controller.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.3
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• pp.39-46
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for the speed control of interior permanent magnet synchronous motor(IPMSM) drive. The design of this algorithm based on FNN controller that is implemented by using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights among the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strongly high performance and robustness in parameter variation, steady-state accuracy and transient response.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.400-401
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• 2018

본 논문에서는 PMSM의 약자속 제어 시에 적용된 과변조 기법에 따른 출력 토크 성능을 비교 및 분석하였다. 기존의 약자속 제어 시 사용되는 동적 과변조 기법 대신 정적 과변조 기법을 적용하는 경우 6-스텝 모드까지 출력 전압의 선형성이 원활하게 유지되어 전동기의 최대 출력 토크 성능을 충분히 활용할 수 있음을 확인하였다.

• Nuclear Engineering and Technology
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• v.21 no.4
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• pp.294-301
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• 1989

The Axial Power Distribution Monitoring System(APDMS) program was developed to calculate a detailed axial power distribution using two-level excore detector, cold leg temperature and control rod position signals. The unnormalized two-level excore detector signals were corrected for the rod shadowing factor determined by control rod position and for the temperature shadowing factor calculated based on cold leg temperature. A shape annealing matrix was then applied to the corrected excore detector response to yield peripheral power. After the core average power was obtained using linear relationship bet-ween core average and peripheral power, the boundary point power correction coefficient was applied to core average power in order to obtain boundary power for both upper and lower core axial boundaries. Then, the axial power distribution was synthesized by spline approximation. In spite of burnup, power level, control rod postion and axial offset changes, the comparisons of axial power distributions between BOXER simulation program and APDMS results showed good agreements within 5% root mean square error for Kori Unit 3 Cycle 4.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.494-499
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• 2013

Based on the state-feedback adaptive neuro-control algorithm for a SISO nonaffine pure-feedback nonlinear system proposed in [15], an output-feedback controller is proposed in this paper. The output-feedback adaptive neural-net controller for the considered nonlinear system has not been previously proposed in any other literatures yet. The proposed output-feedback controller inherits all the advantages of [15] such that it does not adopt backstepping and this results in relatively simple control and adapting laws. Only one neural network is required for the proposed adaptive controller. The proposed neural-net control scheme expands the applicable class of nonlinear systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.3-16
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• 1992

퍼지제어기는 입.출력 관점에서 일반적으로 입.출력에 대한 비선형 함수로 볼수 있다. 전문가의 제어 행위의 입.출력 관계가 크리시(crisp) 비선형 함수로 표현되었을때 그것을 언어적 퍼지 모델링(linguistic fuzzy modelling)하는 방법이 1-입력/ 1-출력 및 2-입력/1-출력의 static 시스템에 대하여 제안되었다. 이를 위해 소속함수 제한조건(membership function constraint)의 개념을 제시하고 선형계획법에 의한 최적화 기법을 이용하여 소속함수의 생성에 관한 체계적인 방법을 제안한다.