• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.343-351
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• 2000

This paper introduces a new rotor position estimation algorithm for the Switched Reluctance Motor, based on the magnetizing curves only at aligned and unaligned rotor positions. The flux linkage is calculated by measured data from phase voltage and phase current, and calculated data are used as the input of magnetizing profiles for rotor position detection. The fuzzy flux observer using novel knowledge-based fuzzy controller are presented to achieve sensorless control of the SRM. The method for selecting optimal angle is proposed for the rotor position detection. The robustness of the proposed algorithm is proved through the comparison of the simulation and experimental results.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.65-66
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• 2007

본 논문은 파라미터 변동에 잘 적응하며 강인한 영구자석 동기전동기의 위치센서 없는 센서리스 제어를 위해 개선된 슬라이딩 모드 관측기에 고정자 저항 추정기능을 추가한 새로운 슬라이딩 모드 적응 관측기를 제안한다. 제안된 관측기는 개선된 슬라이딩 모드 관측기를 사용함으로써 기존의 슬라이딩 모드 관측기에서 채터링(Chattering) 문제 해결을 위해 저역통과필터(Low-pass filter)의 사용 및 추가적인 회전자의 위치보상은 Sigmoid 함수를 스위칭 함수로 사용하므로 제거 할 수가 있다. 또한 고정자 저항 추정기능을 추가하여 센서리스 운행 중 환경적 요인으로 인한 고정자 저항값의 변동이나 초기에 고정자 저항값을 잘못 알고 있더라도 빠른 적응을 통해서 추정오차를 절감시켜 전동기의 속도추정 성능을 향상시킬수 있다. 또한 기존의 적응 슬라이딩 모드 관측기에서의 적분연산을 줄임으로써 제어시스템의 성능을 개선시켰다 제안된 관측기의 안정성은 Lyapunov 후보 함수를 이용하여 관측기의 이득을 설정함으로써 검증하였으며 관측기의 성능은 시뮬레이션을 통한 실험을 통하여 그 타당성을 입증하였다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.3
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• pp.53-61
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• 2006

This paper is proposed adaptive fuzzy-neuro controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. This controller uses fuzzy nile 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 fuzzy-neuro controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2113-2116
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• 1997

The speed sensorless vector control of induction motor using the rotor speed and flux estimation is widely used. In practice, these schemes depend on the accurate parameters of the machine. If in the vector control scheme an inaccurate parameter of induction motor due to skin effects and to temperature variations is used. it is difficult to achieve correct field orientation. From this reason. we propose robust speed sensorless vector control of induction motor against the variations of parameter and disturbance by using extended Kalman filter. For speed and rotor flux estimation. conventional adaptive flux observer is applied. extended Kalman filter which is correctly capable of estimating rotor flux and load by eliminating virtually influences of structural noises is proposed. Simulation results show the effectiveness of the control strategy proposed here for the induction motor drives.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.470-472
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• 1996

In this paper, we proposed a new speed control algorithm based on the least-order observer theory. The proposed system using the new algorithm can estimate the instantaneous speed accurately even at low speed by using a load torgue observer estimating the torgue component of indirect-vector controlled induction motor. Thus the stable characteristics of speed control are possible at low speed even in the case of using low-resolution rotary encoder. Also, the system becomes robust against disturbance by feedforward control the load torque estimated automatically at the speed observer.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.47-50
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• 1998

본 논문은 자동차의 편의성 및 안전성의 동시 확보를 위하여, 보조적 스위치의 조작없이 상시 음성의 입,출력이 가능하도록 하며, band pass filter를 이용하여 잡음환경에서 자동으로 정확하게 음성구간 검출(End Point Detection)을 하게 하였다. Reference Pattern은 Dynamic Multi-Section(DMS)[1] 모델을 사용하였고 차량의 속도에 따라 자동으로 잡음환경에 강인한 모델을 선택하도록 하였으며, 음성의 특징 파라미터와 인식 알고리즘은 Perceptual Linear Predictive(PLP) 13차와 One Stage Dynamic Programming(OSDP)를 사용하였다. 주행중인 자동차 환경(30~70km/h)에서 자주 사용되는 차량제어 명령 33개에 대하여 화자독립 92.98%, 화자종속 94.44% 인식율을 구하였다. 또한 주행중인 차량에서 카폰, 핸드폰 사용으로 인한 사고를 줄이기 위하여 음성으로 전화를 걸 수 있도록 하는 Voice Dialing 기능도 구현하였다.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.142-146
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• 2000

In this paper, we are applied the Genetic Algorithm(GA) to design of the robust $H^{\infty}$ speed controller by auto-tuning of the weighting function. GA is used to design of the weighting functions in the robust $H^{\infty}$ controller. To evaluate the performances of the proposed robust $H^{\infty}$ controller, we make an experiment on $H^{\infty}$ speed controller of an actual DC servo- motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1507-1508
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• 2008

In this paper, we propose a direct robust adaptive backstepping speed controller for induction motors system. A robust adaptive backstepping controller is designed using high order neural networks(HONN), which avoids the singularity problem in adaptive nonlinear control. The stability of the resulting adaptive system with proposed adaptive controller is guaranteed by suitable choosing the design parameter and initial conditions. HONN are used to approximate most of uncertainties which are derived from unknown motor parameters, load torque disturbances and unknown nonlinearities. The applicability of the proposed scheme is tested simulation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.402-410
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• 2019

This paper deals with the disturbance observer (DOB) based sliding mode control (SMC) for a DC motor to control motor rotating speed precisely and to ensure strong robustness against disturbance including load torque and parameter variation. The reason of steady state error in speed on conventional SMC without DOB is analyzed in detail. Especially, the suggested DOB is designed to prevent measuring noise and harmonics caused by derivative operation on rotating speed. The control performance of the DOB based SMC is evaluated by the various simulations. The simulation results showed that the DOB based SMC had more robust performance than the SMC system without DOB. Especially, precise speed control was possible even though motor parameter variation and load torque was added to the system.