• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1527-1539
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• 2015

In this paper the hardware implementation of the direct torque control based on the fuzzy logic technique of induction motor on the Field-Programmable Gate Array (FPGA) is presented. Due to its complexity, the fuzzy logic technique implemented on a digital system like the DSP (Digital Signal Processor) and microcontroller is characterized by a calculating delay. This delay is due to the processing speed which depends on the system complexity. The limitation of these solutions is inevitable. To solve this problem, an alternative digital solution is used, based on the FPGA, which is characterized by a fast processing speed, to take the advantage of the performances of the fuzzy logic technique in spite of its complex computation. The Conventional Direct Torque Control (CDTC) of the induction machine faces problems, like the high stator flux, electromagnetic torque ripples, and stator current distortions. To overcome the CDTC problems many methods are used such as the space vector modulation which is sensitive to the parameters variations of the machine, the increase in the switches inverter number which increases the cost of the inverter, and the artificial intelligence. In this paper an intelligent technique based on the fuzzy logic is used because it is allows controlling the systems without knowing the mathematical model. Also, we use a new method based on the Xilinx system generator for the hardware implementation of Direct Torque Fuzzy Control (DTFC) on the FPGA. The simulation results of the DTFC are compared to those of the CDTC. The comparison results illustrate the reduction in the torque and stator flux ripples of the DTFC and show the Xilinx Virtex V FPGA performances in terms of execution time.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 추계학술대회 논문집
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• pp.215-216
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• 2015

A suspending force control based on fuzzy logic control is proposed to apply on a novel hybrid bearingless switched reluctance motor(BLSRM) which has separated torque and suspending force pole. In this paper, two fuzzy controller targeted at x-axis direction and y-axis direction are adopted to maintain the shaft at center position, which is very necessary for stable operation of BLSRM. Useing the modified fuzzy logic controller, the suspending system can behave a good performance, and the proposed scheme can be verified by simulation results.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.166-171
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• 1996

Generally, when we control the robot, we should calculate exactly Inverse Kinematics. However, Inverse Kinematics calculation is complex and it takes much time for the manipulator to control in real-time. Therefore, the calculation of Inverse Kinematics can result in significant control delay in real time. In this paper, we will present that Inverse Kinematics can be calculated through Fuzzy Logic Mapping, Based on an exact solution through fuzzy reasoning instead of Inverse Kinematics calculation Also, the result provides sufficient precision and transient tracking error can be controlled based on a fuzzy adaptive scheme proposed in this paper. Based on the Denavit-Hartenberg parameters specification, after the Jacobian matrix of arbitrary manipulator is calculated, we will construct Fuzzy Inverse Kinematics Mapping(FIKM) using fuzzy logic and represent a good control efficiency through simulation of 2-DOF manipulator.

• 연구논문집
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• 통권23호
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.

• 한국정보과학회논문지:정보통신
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• 제31권3호
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• pp.289-297
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• 2004

최신 무선 통신망은 이동 단말의 동적 재배치를 허용하므로 입력 호를 전달하기 위해서는 이동 단말의 트랙을 관리하는 위치 관리 메커니즘이 필요하다 본 논문에서는 페이징 비용을 감소시키기 위하여 퍼지 논리 기반 선택적 페이징 방법을 제안한다. 퍼지 논리 기반 위치 관리 방법에서, 위치 갱신은 방향 기반 방법과 이동 기반 방법을 혼용한 지역 기반 방법을 사용하고, 위치 검색은 이동 단말의 이동성 정보에 기초한 퍼지 논리 기반 선택적 페이징 방법을 사용한다. 부분 후보 페이징 지역이 퍼지 논리 제어에 의해 선택되고, 퍼지 논리 기반 선택적 페이징 방법은 그 부분 후보 페이징 지역 내의 셀들만 페이지 한다. 제안하는 퍼지 논리 기반 위치 관리 방법의 성능을 분석적 모델과 모의실험을 통하여 평가하고, 그것의 성능을 LA 및 BVP와 비교한다. 평가 결과, 제안하는 퍼지 논리 기반 위치 관리 방법이 다른 위치 관리 방법에 비해 우수한 성능을 제공함을 알 수 있었다.

• 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.

• 한국컴퓨터산업학회논문지
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• 제3권1호
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• pp.95-104
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• 2002

본 논문은 ATM(Asynchronous Transfer Mode) 서비스 분류 중 UBR(Unspecified Bit Rate)과 ABR(Available Bit Rate)상에서의 인터넷 TCP/IP(Transmission Control Protocol-Internet Protocol) 트래픽에 관한 연구이다. 퍼지 논리 예측은 트래픽 처리량의 효율성과 공정성을 개선하는 데 사용된다. 본 논문에서는 TCP/IP에서 셀 제거 방식에 기반한 UBR 서비스 버퍼 방식으로 퍼지 논리를 사용하였다. 이는 퍼지 논리 선택적 셀 제거 방식이라고 부른다. 이 방식의 주요 특징은 스위치의 차후 예측 버퍼 상태에 따라서 동적으로 새로 들어오는 패킷을 수락할 것인지 제거할 것인지를 결정한다는 것이다. 이는 제거 인수의 산출을 위해 퍼지 논리 예측의 사용으로 수행된다. 패킷 제거 결정은 이러한 제거 인수와 예측 초기값에 의해 결정된다. 시뮬레이션을 수행하여 제안된 방식이 TCP/IP의 효율성과 공정성 측면에서 현저하게 개선된 것을 알 수 있다. ABR 서비스에서 TCP/IP를 연구하기 위하여 퍼지 논리 ABR 서비스 버퍼 관리 방식을 이전의 연구로부터 근접하거나 정확한 공정율 계산 ER(Explicit cell Rate) 스위치 알고리즘에 적용하였다. 그리하여 기존의 방식과 퍼지 논리 제어 방식의 성능을 비교하였다. 시뮬레이션 결과는 TCP 패킷 손실율이 0이고, 퍼지 논리 제어 방식이 최대한의 효과를 내며 작은 버퍼 크기로 완벽한 공정성을 갖는 것을 보여준다. 퍼지 논리 제어 방식은 VBR 트래픽과 혼용되었었을 때 낮은 셀 손실을 갖고 보다 높은 효율성을 보여준다.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.80-83
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• 2003

A Genetic algorithm is a searching algorithm that based on the law of the survival of the fittest. Multi-population Genetic Algorithms are a modified form of genetic algorithm. Therefore, experience with fuzzy logic and genetic algorithm has proven to be that a combination of them can efficiently make up for their own deficiency. The Multi-population Genetic Algorithms independently evolve subpopulations. In this paper, we suggest a new coding method that independently evolves subpopulations using the fuzzy logic controller. The fuzzy logic controller has applied two fuzzy logic controllers that are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The migration scheme in the multi-population genetic algorithms using fuzzy logic controllers is tested for a function optimization problem, and compared with other group migration schemes, therefore the groups migration scheme is then performed. The results demonstrate that the migration scheme in the multi-population genetic algorithms using fuzzy logic controller has a much better performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1687-1692
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• 1991

Burrs, created when metals deform plastically, are by-products of most machining processes. The increasing requirements of precision and reliability in manufacturing processes have led to the development of systems for automated deburring. In this paper the motivations and requirements for automated robotic deburring are discussed. Also, the feasibility of automating the deburring process using fuzzy logic controller is investigated. In implementing the fuzzy logic controller, particular attention is paid to the acoustic emission sensing for the characterization and feedback control of the burr removal process. The results of the experiments reveal the rule based control scheme based on fuzzy logics can be a good alternative to traditional control schemes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.184-187
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• 1996

In this paper, an algorithm for tuning gains of a PID controller is proposed. The proposed algorithm is composed of two stages. The first is a stage for Lyapunov function-based initial stabilization of an overall system and rough tuning gains of the PID controller. The other is that for fine tuning gains of the PID controller. All tunings are performed by using the well-known fuzzy logic-based tuner. The computer simulations are performed to show the validity of the proposed algorithm and results are presented.