• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 하계학술대회 논문집 B
• /
• pp.1248-1250
• /
• 2004

This paper is proposed adaptive fuzzy-neural network controller(NFC) for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on NFC that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive NFC is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
• /
• pp.524-527
• /
• 2003

This paper proposes speed control system using a Fuzzy Logic Controller(FLC) in order to realize the speed control of Permanent Magnet AC Motor with no sensor. FLC based MRAS(Model Reference Adaptive System) estimates the speed of Permanent Magnet AC Motor. Using the estimated speed, speed control is performed. The experiment is executed to verify the propriety and the effectiveness of the proposed system.

• 한국조명전기설비학회지:조명전기설비
• /
• 제11권4호
• /
• pp.82-91
• /
• 1997

I보일러-터빈 설비는 화력발전소의 주전원설비 내지 자가발전설비로서 보일러는 연료를 연소시켜 그 열을 수관내의 물에 전달하여 필요한 증기를 얻는 설비이고, 터빈은 보일러에서 보내온 고온, 고압의 증기를 팽창시켜 기계적 에너지로 변환하여 그 에너지로 발전기를 회전하여 전기를 얻는 장치이다. 보일러-터빈 설비는 전기적 출력과 드럼내의 증기압 및 수위를 적절히 조절함으로써 발전소의 안정된 운전을 도모하고 발전용 연료의 절감 및 이를 통한 공해 저감을 이루어야 할 필요가 있다. 본 논문에서는 이런 보일러-터빈 설비에 대한 제어시스템을 설계하는 한 방법으로서 기준모델 추종형 퍼지 시스템을 제안한다. 보일러-터빈 설비는 다변수 비선형 시스템으로서 일반적인 제어시스템 구성이 힘들지만, 오버슈트가 없으며 속응성이 좋은 기준모델을 선정하고 이 기준모델을 추종하도록 하는데 일반적인 1입력-1출력 퍼지제어기만을 적용하여도 기준신호에 대한 추종성 및 외란제거 능력 그리고 모델링 오차에 대한 강인성까지 나타내는 제어시스템의 설계가 가능하게 되었다. 따라서 전원설비로서의 보일러-터빈 설비에 대한 효율적인 제어시스템 설계방법으로 활용될 수 있을 것이다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제53권6호
• /
• pp.389-394
• /
• 2004

This paper proposes a speed estimation method using FLC(Fuzzy Logic Controller) in order to realize the speed control of PMAM(Permanent Magnet AC Motor) with no speed sensor. This method uses FLC as a adaptive laws of MRAS(Model Reference Adaptive System) and estimates the rotor speed of PMAM with a difference between the reference model and the adjustable model. Speed control is performed by PI controller with the estimated speed. The experiment is executed to verify the propriety and the effectiveness of the proposed system.

• International Journal of Control, Automation, and Systems
• /
• 제3권4호
• /
• pp.552-563
• /
• 2005

In this paper, we propose a wavelet based fuzzy neural network (WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges the advantages of the neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of the wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of a mobile robot via the gradient descent (GD) method. In addition, an approach that uses adaptive learning rates for training of the WFNN controller is driven via a Lyapunov stability analysis to guarantee fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control results of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• 대한기계학회논문집A
• /
• 제23권6호
• /
• pp.931-942
• /
• 1999

This paper develops a 3 DOF vehicle model which includes lateral, roll and yaw motion to study a 4WS vehicle. The model is used for the simulation of a 4WS vehicle behavior, and to derive a control algorithm for rear wheel steering. This paper uses a feedforward plus feedback control scheme to compute a rear wheel steering angle. The feedforward control scheme for computing the first rear wheel steering angle uses a gain which is acquired by multiplying a proper value on a gain to maintain a zero sideslip angle. The feedback control scheme for computing the second rear wheel steering angle uses fuzzy logic and model following control scheme. A linear 2 DOF model is used as a reference model for model following control, and is derived from the developed 3 DOF model by neglecting sprung mass roll motion. A reference state variable is yaw rate, and is computed using the linear 2 DOF model. J-turn and lane change maneuver simulation are performed to show the effectiveness of the developed control scheme. The simulation results show that the 4WS vehicle with the developed control scheme has much better performance in yaw rate, lateral acceleration, roll angle, and sideslip angle than the 2WS vehicle. Also, the results show that the performance of the developed control is close to the one of an optimal control which assumes all states are perfect.

• Journal of Power Electronics
• /
• 제7권2호
• /
• pp.159-173
• /
• 2007

In this paper, an intelligent sliding-mode position controller (ISMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a sliding-mode position controller (SMC) in the position feed-back loop in addition to an on-line trained fuzzy-neural-network model-following controller (FNNMFC) in the feedforward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with on-line learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the sliding-mode position controller are described with a second order switching surface (PID) which is insensitive to parameter uncertainties and external load disturbances. To realize high dynamic performance in disturbance rejection and tracking characteristics, an on-line trained FNNMFC is proposed. The connective weights and membership functions of the FNNMFC are trained on-line according to the model-following error between the outputs of the reference model and the PMSM servo drive system. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode position controller. The results confirm that the proposed ISMC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.67.3-67
• /
• 2001

A fuzzy control strategy is described which is utilized to control the joint angle and tip deflection in single flexible manipulator. In this paper, an existing model for a single flexible manipulator is used f3r the initial development of an FLC. One FLC is designed to govern the joint angle of the manipulator as it is rotated from one position to another, and a second FLC is designed to attenuate the tip deflection which result from joint angle body motion. Reference Trajectory Command is an important method to reduce vibration in flexible beam. This paper presents a very simple command control shaping which eliminates multiple mode residual vibration in a flexible beam combined fuzzy controller ...

• 대한전기학회논문지:시스템및제어부문D
• /
• 제51권12호
• /
• pp.535-541
• /
• 2002

This paper proposes an adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drive. In the proposed system, fuzzy control is sued to implement the direct controller as well as the adaptation mechanism. The adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed controller is confirmed by performance results for PMSM drive system.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1478-1481
• /
• 2005

As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network 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 analysis results to verify the effectiveness of the new method.