• 전기학회논문지P
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• 제67권3호
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• pp.143-148
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• 2018

In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.215-219
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• 1998

This paper presents a practical application of fuzzy logic control to temperature control of glass melting furnace. Due to the characteristics of glass melting furnace, a hybrid algorithm of conventional PI controller and fuzzy logic controller is proposed and discussed. Practical implementation results of the production furnace showed the effectiveness of the proposed control algorithm.

• International Journal of Automotive Technology
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• 제6권5호
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• pp.529-536
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• 2005

This paper presents a novel design of a fuzzy control strategy (FCS) based on torque distribution for parallel hybrid electric vehicles (HEVs). An empirical load-regulating vehicle operation strategy is developed on the basis of analysis of the components efficiency map data and the overall energy conversion efficiency. The aim of the strategy is to optimize the fuel economy and balance the battery state-of-charge (SOC), while satisfying the vehicle performance and drivability requirements. In order to accomplish this strategy, a fuzzy inference engine with a rule-base extracted from the empirical strategy is designed, which works as the kernel of a fuzzy torque distribution controller to determine the optimal distribution of the driver torque request between the engine and the motor. Simulation results reveal that compared with the conventional strategy which uses precise threshold parameters the proposed FCS improves fuel economy as well as maintains better battery SOC within its operation range.

• 한국전산구조공학회논문집
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• 제22권2호
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• pp.135-144
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• 2009

본 연구에서는 초고층건물의 풍응답을 저감시키기 위하여 스마트 TMD(STMD)를 활용한 퍼지 하이브리드 제어기법을 제안하였다. 효과적인 제어알고리즘을 개발하기 위하여 STMD의 응답저감에 우수한 성능을 보이는 스카이훅(skyhook) 제어기와 구조물의 응답저감에 뛰어난 그라운드훅(groundhook) 제어알고리즘을 사용하였다. 본 연구에서는 두 제어기를 적절히 조합하기 위하여 최적의 가중치를 실시간으로 결정하는 퍼지 하이브리드 제어기를 개발함으로써 일반적인 가중합방식의 하이브리드 제어기법의 성능을 개선하였다 제안된 제어기의 성능을 검토하기 위하여 풍하중을 받는 76층 사무소 건물을 예제구조물로 사용하였다. MR감쇠기를 이용하여 STMD를 구성하였고, STMD의 제어성능을 평가하기 위하여 TMD및 ATMD의 성능과 비교하였다. 수치해석을 통하여 STMD의 제어성능이 TMD에 비하여 월등히 뛰어남을 확인할 수 있었다. 또한 퍼지 하이브리드 제어기법을 사용하면 스카이훅 및 그라운드훅 제어기를 효과적으로 조합하여 STMD와 건물의 응답을 동시에 줄일 수 있음을 확인하였다.

• International Journal of Quality Innovation
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• 제5권1호
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• pp.52-67
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• 2004

Successful implementation of statistical process control techniques requires for operational definitions and precise measurements. Nevertheless, very often analysts can dispose of process data available only by linguistic terms, that would be a waste to neglect just because of their intrinsic vagueness. Thus a hybrid approach, which integrates fuzzy set theory and common statistical tools, sounds useful in order to improve effectiveness of statistical process control in such a case. In this work, a fuzzy approach is adopted to manage linguistic information, and the use of a Chi-squared control chart is proposed to monitor process performance.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.192-197
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• 2007

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.260-262
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• 2006

This paper presents Hybrid-PI controller of induction motor drive using fuzzy control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid-PI controller proposes a new method based self tuning PI controller. Hybrid-PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.994-998
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• 1996

We propose an approach to integrating fuzzy logic control with RBF(Radial Basis Function) networks and show how the integrated network can be applied to multivariable self-organizing and self-learning fuzzy controller. Using the hybrid learning algorithm. To investigate its usefulness and performance, this controller is applied to a time-delayed process system. Simulation results show good control performance and fast convergency in hybrid loaming method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.129.5-129
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• 2001

When a robot manipulator performs some task like grinding or assembling, not only the position control but also the force control of the tools connected to the robot must be controlled. But at this time We were received the uncertainty problems of system information for the force control, for example disturbance, senor resolution and measurement noise. Therefore we proposed fuzzy logic control method instead of existing control theory for the robot manipulator control, for example PID control method. In this paper, We proposed hybrid position/force control of robot manipulator using fuzzy logic control method. To show the validity of the proposed fuzzy controller, We compared fuzzy controller with conventional PID controller.

• 한국산업융합학회 논문집
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• 제19권3호
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• pp.101-108
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• 2016

I propose a hybrid fuzzy controller with a look-up table to improve the performance of the FARMA(Fuzzy Auto-regressive Moving Average) fuzzy controller. The hybrid structure of the proposed method is composed of a fuzzy controller with a look-up table of the PD type and the FARMA fuzzy controller. The proposed method improves poor performance due to the lack of I/O data to calculate predictive output and shows robust performance over the FARMA fuzzy controller when a incorrect Dmax value is selected by trial and error. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results with those of the FARMA fuzzy controller.