• 조명전기설비학회논문지
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• 제25권5호
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.

• Journal of Electrical Engineering and Technology
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• 제4권4호
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• pp.429-437
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• 2009

This paper proposes a hybrid voltage controller based on a hierarchical control structure for implementation in the Jeju power system. The hybrid voltage controller utilizes the coordination of various reactive power devices such as generators, switched shunt devices and LTC to regulate the pilot voltage of an area or zone. The reactive power source can be classified into two groups based on action characteristics, namely continuous and discrete. The controller, which regulates the pilot bus voltage, reflects these characteristics in the coordination of the two types of reactive power source. However, the continuous type source like generators is a more important source than the discrete type for an emergency state such as a voltage collapse, thereby requiring a more reactive power reserve of the continuous type to be utilized in the coordination in order to regulate the pilot bus voltage. Results show that the hybrid controller, when compared to conventional methods, has a considerable improvement in performance when adopted to control the pilot bus voltage of the Jeju island system.

• 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.

• 전력전자학회논문지
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• 제23권2호
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• pp.112-120
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• 2018

This work presents a hybrid generator, which is a combination of a permanent magnet (PM) and winding structure with a PM exciter. The field winding of the proposed hybrid generator is fed by the PM exciter and the embedded current controller, which is installed in the generator shaft. In the no-load condition, the output voltage of the generator is produced by the PM flux of the generator without any field winding current. The field winding current produces an insufficient flux to retain the output voltage of the generator when the load is injected. The total efficiency can be increased from the PM exciter and PM flux of the generator. The field current has to be controlled inside the proposed generator. The generated power from the PM exciter is used to excite the field flux of the generator. The embedded current controller is commanded by the external voltage controller using the infrared wireless method. The 10 kW prototype hybrid PM generator is designed and tested to verify the effectiveness of the proposed system. The experimental results are compared with those of the winding generator with PM exciter.

• Journal of Power Electronics
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• 제5권2호
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• pp.129-141
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• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• 한국산학기술학회논문지
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• 제7권5호
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• pp.823-829
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• 2006

본 논문에서는 기존의 PID 제어기의 P 부분만을 퍼지 논리제어기로 대체한 퍼지 P+ID 제어기를 제안하였으며. 제안된 퍼지 P+ID 제어기는 단지 하나의 제어파라미터만을 추가하여 기존 PID 제어기를 조절하기 때문에 쉽게 설계 할 수 있으며, PID 제어기의 구조를 유지함으로서 기존 장치의 하드웨어 부분을 수정할 필요가 없다. 또한, 퍼지 P+ID 제어기는 기존 PID 제어기와 비교해서 충분한 안정성을 보여주며, 구조가 단순하고 계산 량이 적어 제어기의 동조시간을 기존의 퍼지 제어기에 비해서 많이 줄일 수 있는 장점이 있다. 제안된 Fuzzy P+ID 제어기를 BLDC 모터에 적용하여, 시뮬레이션 및 실험을 통하여 본 논문에서 제안한 제어기가 기존의 제어기보다 제어성능이 우수함을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.207-209
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• 1995

The PID controller is widely used due to its fast response and robustness. But its performance is not so good compared with modem controllers such as adaptive, robust, fuzzy, neural controller. Therefore, it is natural to replace PID controller by modem controllers. But, the problem is that modem controller can not be easily applied to the real time process. Hence, this paper proposes such a structure that PID controller and Self-Learning Fuzzy Controller(SLFC) are in parallel with each other. The parameter of SLFC will be updated by gradient descent method using neuro - identifier. The usefulness of this hybrid controller will be proved by simulation results.

• 드라이브 ㆍ 컨트롤
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• 제17권4호
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• pp.80-86
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• 2020

Autonomous driving is one of the most important new technologies of our time; it has benefits in terms of safety, the environment, and economic issues. Path following algorithms, such as automated lane keeping systems (ALKSs), are key level 3 or higher functions of autonomous driving. Pure-Pursuit and Stanley controllers are widely used because of their good path tracking performance and simplicity. However, with the Pure-Pursuit controller, corner cutting behavior occurs on curved roads, and the Stanley controller has a risk of divergence depending on the response of the steering system. In this study, we use the advantages of each controller to propose a hybrid control strategy that can be stably applied to complex driving environments. The weight of each controller is determined from the global and local curvature indexes calculated from HD map information and the current driving speed. Our experimental results demonstrate the ability of the hybrid controller, which had a cross-track error of under 0.1 m in a virtual environment that simulates K-City, with complex driving environments such as urban areas, community roads, and high-speed driving roads.

• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1014-1022
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• 2002

An objective of Automated Highway Systems (AHS) is to increase the safety and throughput of the existing highway infrastructure by introducing traffic automation. AHS is an example of a large scale, multiagent complex dynamical system and is ideally suited for a hierarchical hybrid controller. We discuss a design issue of efficient hybrid controllers for the platoon maneuvers on AHS. For the modeling of a hybrid system including the merge and split operations, a safety distance policy is introduced for the merge and split operations. After that, the platoon system will be modeled by a hybrid system In addition, a hybrid controller for the proposed merge and split operation models is presented. Finally, the performance of the proposed hybrid control scheme is demonstrated via scenarios for platoon maneuvers.

• 전력전자학회논문지
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• 제5권4호
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• pp.352-357
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• 2000

벡터제어기법은 유도전동기의 고성능 운전을 위해 널리 사용되고 있다. 벡터제어기법을 사용해 전동기의 속도제어를 행할 정우 전동기의 속도나 전류를 제어하기 위해 주로 PI제어기가 사용되고 있다. 이 경우 유도전동기의 동 특성은 PI제어기의 이득과 밀접한 관계를 갖고 있으며 유도전동기의 고성능제어를 위해서는 PI제어기의 이득을 최적화 시킬 필요가 있다. 그러나 PI제어기의 이득을 최적화 시키기 위해서는 전동기제이 시스템의 등가모델을 정확히 알아야 하기 때문에 변동 부하조건하에서 일관성 있는 최적 이득값을 얻기란 대단히 힘들다. 본 논문에서는 이러한 PI제어기의 단점을 보완하기 위해 과도상태만을 제어하기 위한 간략화된 퍼지제어기와 정상상태 제어를 위한 기존의 PI제어기를 병렬로 구성한 하이브리드 제어기를 제안하고 이를 실제 유도전동기의 벡터제어에 적용하여 알고리즘의 타당성을 검증하였다.