• 전기전자학회논문지
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• 제13권3호
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• pp.32-38
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• 2009

Ultrasonic motor (USM) is a new type motor which is driven by the ultrasonic vibration of piezoelectric elements. It possess many useful features that electromagnetic motors do not have, such as low speed and high torque. However, ultrasonic motor has heavy nonlinear speed characteristics and is sensitive to the change of drive conditions. In order to solve these problems, we present a smooth position control scheme for ultrasonic motor using fuzzy logic control with human expertise and without the need of any precise mathematical model. A "smooth operation" consideration is included when constructing the fuzzy rule base in order to achieve a most smooth response. An experimental position control system is constructed to show the effectiveness of the proposed control scheme.

• 한국정밀공학회지
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• 제18권10호
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• pp.161-167
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• 2001

This paper presents an approach to nonlinear engine idle controller and intake manifold absolute pressure(MAP) observer based on mean torque production model. A stable engine idle speed is important in that the unstable engine Idle mode can make engine to drooping or stall state. A sliding fuzzy controller has been designed to control engine idle speed under load disturbance. A sliding observer is also developed to estimate the intake manifold absolute pressure and compared with the actual MAP sensor value. The sliding mode observer has shown good robustness and good tracking performance. The inputs of sliding fuzzy controller are the errors of rpm and MAP. The output is a duty cycle(DC) for driving a idle speed control valve(ISCV).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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• pp.331-333
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• 1995

A high performance motor drive system must have a good speed command tracking, a insensitivity to a parameter variation and sampling time. In this paper, a robust speed controller for an induction motor is proposed. The speed controller is fuzzy-sliding adaptive controller and its system continuously is varied. That is, only P gain act in dynamic state, I gain in steady-state. Because this system is a sort of adaptive control system, global stability analysis is used to Lyapunov function. Consequently, in this paper application of fuzzy sliding adaptive controller to induction motor controlled by vecter control is presented and the control system is digitally implemented within DSP.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권10호
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.111.1-111
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• 2001

In this paper, a robust speed control is proposed for Permanent Magnet Synchronous Motor system. PMSM without reduction gear has been widely used in high performance application such as robots and machine tools. It is well known that the control performance of the PMSM is very sensitive to load disturbance and system parameter variation. The idea of the proposed speed controller based on combination of sliding mode control with fuzzy gain scheduling. The sliding mode controller leads to fast system dynamics of slight sensitivity to the load disturbance and system parameter variations, the fuzzy gain scheduling mechanism reduces the chattering phenomenon. The simulation results have proved that the proposed control scheme provides a robust control performance under load disturbance and system parameter variation.

• 전력전자학회논문지
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• 제4권3호
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• pp.240-248
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• 1999

본 논문에서는 SRM의 가변속 구동을 위한 퍼지 논리제어기를 제안한다. SRM은 높은 비선형 특성을 갖으며 토크 출력을 극대화하기 위해 포화영역에서 동작한다. 거시적 제어와 미시적 제어를 갖는 퍼지 제어기를 포함하는 높은 비선형 SRM 구동 시스템을 모델링 하기 위한 체계적인 접근이 제시되었다. 속도변화와 외란의 동적 특성을 통해 폭넓은 동작 범위조건에 대한 SRM의 성능해석이 제시되었다. 퍼지제어기에 의해 구동되는 SRM 시스템은 그 장점을 나타내기 위해 종래의 제어기와 비교되었다. 제안된 퍼지제어기의 속도변화와 외란에 대한 동작을 확인하기 위해서 실험결과가 제시되었다.

• 전력전자학회논문지
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• 제15권4호
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• pp.282-287
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• 2010

본 논문에서는 영구자석 동기전동기(PMSM)를 위한 비선형 속도제어기와 Takagi-Sugeno 퍼지 기법을 이용한 퍼지 부하 토크관측기를 제안한다. 또한 제안된 비선형 속도제어기와 퍼지 토크관측기가 존재하기 위한 LMI 조건을 유도하고, 제어기와 관측기의 이득 행렬을 계산하기 위한 선형 행렬 부등식(LMI) 매개변수화가 주어진다. 제안된 비선형 속도제어기와 퍼지 부하 토크관측기의 성능을 검증하기 위하여, 모터 파라미터 및 부하 토크 변동 하에서 시뮬레이션 및 실험 결과가 주어졌다.

• 전기학회논문지
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• 제60권9호
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• pp.1700-1707
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• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• 드라이브 ㆍ 컨트롤
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• 제15권1호
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• pp.28-37
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• 2018

When the wind speed rises above the rated wind speed, the produced power of the wind turbines exceeds the rated power. Even more, the excessive power results in the undesirable mechanical load and fatigue. A solution to this problem is pitch control of the wind turbines. This paper presents a systematic design method of a collective pitch controller for the wind turbines using a discrete fuzzy Proportional-Integral (PI) controller. Unlike conventional PI controllers, the fuzzy PI controller has variable gains according to its input variables. Generally, tuning the parameters of fuzzy PI controller is complex due to the presence of too many parameters strongly coupled. In this paper, a systematic method for the fuzzy PI controller is presented. First, we show the fact that the fuzzy PI controller is a superset of the PI controller in the discrete-time domain and the initial parameters of the fuzzy PI controller is selected by using this relationship. Second, for simplicity of the design, we use only four rules to construct nonlinear fuzzy control surface. The tuning parameters of the proposed fuzzy PI controller are also obtained by the aforementioned relationship between the PI controller and the fuzzy PI controller. As a result, unlike the PI controller, the proposed fuzzy PI controller has variable gains which allow the pitch control system to operate in broader operating regions. The effectiveness of the proposed controller is verified with computer simulations using FAST, a NREL's primary computer-aided engineering tool for horizontal axis wind turbines.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.176-178
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• 2004

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed.