• 한국지능시스템학회논문지
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• 제22권6호
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• pp.700-705
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• 2012

본 논문은 미리 설계된 타카기-수게노 퍼지 모델 기반 아날로그 제어기를 상태 정합의 의미에서 등가인 샘플치 제어기로 효율적으로 변환하기 위해, 관측기 기반 출력 궤환 퍼지 제어기에 대한 지능형 디지털 재설계 기법을 제안한다. 아날로그 제어 시스템과 샘플치 제어 시스템 사이의 점근적 연관성을 위해 델타 연산자를 사용한다. 지능형 디지털 재설계 문제는 정합될 선형 연산자 간의 놈의 거리를 최소화하는 문제로 생각한다. 제어기 설계 조건은 선형행렬부등식의 형태로 유도되며, 디지털 재설계시 관측기와 제어기에 대한 분리 설계 조건이 만족함을 보인다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 전기설비전문위원
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• pp.74-76
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• 2009

In this paper, search method and sliding mode observer are developed for efficiency optimization of induction motor. The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. The search controller is based on the "Rosenbrock" method and finds the flux level at the minimum input power of induction motor. Once this optimal flux level has been determined, this information is utilized to update the rule base of a fuzzy controller A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is also used to compensate for mechanical uncertainties in the speed control of induction motor. Simulation results are presented to validate the proposed controller.

• 한국정보통신학회논문지
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• 제19권4호
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• pp.973-983
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• 2015

본 논문에서는 부하외란이 존재하는 경우에 T-S 퍼지모델을 이용한 비선형 외란 관측기를 제안함으로써 IPMSM(Interior Permanent Magnet Motor)의 제어성능 향상을 도모하였다. T-S퍼지모델은 국부선형모델들의 퍼지결합으로 비선형계통을 T-S퍼지모델을 구한 다음, 각 국부선형모델의 역함수에 대한 T-S퍼지모델을 구함으로써 비선형 역함수를 구하는 방법을 제안하였다. 역함수를 이용한 외란관측기의 구성은 선형계통에서와는 달리 비선형 계통에서는 용이하지 않으나 T-S퍼지 모델을 사용함으로써 이 문제를 해결한 것이다. 제안된 비선형 외란관측기는 T-S퍼지제어기의 대표 격인 PDC 제어기와 함께 사용되었고 시뮬레이션을 통해서 그 유용성을 입증하였다.

• 전력전자학회논문지
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• 제5권4호
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• pp.343-351
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• 2000

본 논문에서는 정렬과 비정렬된 회전자 위치들에서 자화곡선들을 기본으로 한 SRM의 회전자 워치펑가 알고리즘을 제안한다. 자화곡선은 측정된 상 전압과 상 전류로부터 계산되어지고, 계산된 데이타는 회전자 위치검출을 위한 자화곡선의 입력으로 사용되어진다. 자화곡선은 비션형 특성해석에 적합한 퍼지 알고리즘으로 구생되어졌다. 종래의 지삭기반 퍼지제어기를 이용한 자속관측기가 SRM의 센서리스 제어를 얻기 위해 제시되었다. 최적 각을 선정하기 위한 방식이 회전자 위치검출을 위해 제시되었다. 제안된 알고리즘의 강인성이 시뮬레이션과 실험결과의 비교를 통해 입증되었다.

• 전기학회논문지P
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• 제54권2호
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• pp.73-79
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• 2005

This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Journal of Power Electronics
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• 제8권3호
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• pp.280-290
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• 2008

This paper deals with an investigation and evaluation of the performance of a state observer based Permanent Magnet Synchronous Motor (PMSM) drive controlled by PI (Proportional Integral), PID (Proportional Integral and Derivative), SMC (sliding mode control), ANN (Artificial neural network) and FLC (Fuzzy logic) speed controllers. A detailed study of the steady state and dynamic performance of estimated speed and angle is given to demonstrate the capability of the controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1754-1757
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• 2004

For the anti-sway control of traveling cranes, there are several solutions, i.e., by fuzzy control, by optimal control theory, etc. Each of them is reported to be effective. And, H infinity control and $H_2$ control can be also used. However, the full order observer which estimates all states in the controlled object is used in these methods. Therefore, the orders of these controllers are apt to be higher than that of the optimal controller, etc. Because the conventional H2 controller which minimizes $H_2$ norm consists of two parts, that is: feedback gains which make the controlled object stable and the full order observer which estimate those states. If the minimal order observer is used instead of the full order one, the order of the controller can be reduced. In this paper, we propose a new method based on the minimalization of $H_2$ norm using the minimal order observer. And, we confirm the effect of a new $H_2$ controller in the experiments of the anti-sway control of a traveling crane.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1775-1776
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• 2008

This paper presents a adaptive fuzzy control suitable for motion control of multi-link robot manipulators with uncertainties. When joint velocities are available, full state adaptive fuzzy feedback control is designed to ensure the stability of the closed loop dynamic. If the joint velocities are not measurable, an observer is introduced and an adaptive output feedback control is designed based on the estimated velocities. To reduce the number of fuzzy rules of the fuzzy controller, we consider the properties of robot dynamics and the decomposition of the unknown input gain matrix. The proposed controller is robust against uncertainties and external disturbances. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator.

• Journal of Information Processing Systems
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• 제18권4호
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• pp.510-523
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• 2022

Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of two-wheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.179-181
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• 2004

This paper is proposed an adaptive fuzzy-neural network(A-FNN) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using A closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.