• Journal of Electrical Engineering and information Science
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• 제2권3호
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• pp.113-122
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• 1997

An adaptive input-output linearization technique for a robust speed control of a brushless C(BLDC) motor is presented. By using this technique, the nonlinear moro model can be effectively linearized in Brunovski canonical form, an 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 caused by the incomplete linearization. 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 nd 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 simualtions and experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.280-282
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• 1994

This paper proposes sliding mode state for robust speed control of induction motor. Sliding mode state observer is robust for measurement noise, modeling-error and load disturbance. The pole of sliding mode state observer can be placed at (0,0) in Z-plane for fast response. This method is, namely, deadbeat control. Sliding mode state observer output is discontinuous on a switching hyperplance, that causes harmful effects such as current harmonics and speed oscillation. In this paper, also the reducing method of the chattering of sliding mode state observer output is proposed. The proposed system is digitally implemented with TMS320C31.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Journal of Power Electronics
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• 제11권6호
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• pp.819-823
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• 2011

This paper presents a fuzzy PD speed control scheme for the robust speed tracking of a permanent magnet synchronous motor (PMSM). Motivated by the common control engineering knowledge that transient performance can be improved if the P gain is big and the D gain is small in the beginning, a linearizing control scheme with a fuzzy PD controller is proposed. The global system stability is analyzed and the proposed control algorithm is implemented using a TMS320F28335 DSP. Simulation and experimental results are given to verify the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• 제5권1호
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• pp.129-139
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• 2010

To be satisfied with complex load condition of electric vehicle, fuzzy logic control (FLC) is applied to improve speed response and system robust performance of induction traction machine based on indirect rotor field orientation control. The proposed propulsion system consists of two induction motors (IM) that ensure the drive of the two back driving wheels of lightweight electric vehicle by means the vehicle used for passenger transportation. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling, independently, every driving wheel to turn at different speeds in any curve. Our electric vehicle fuzzy inference system control's simulated in Matlab SIMULINK environment, the results obtained present the efficiency and the robustness of the proposed control with good performances compared with the traditional PI speed control, the FLC induction traction machine presents not only good steady characteristic, but with no overshoot too.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.139.4-139
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• 2001

The thesis propose the sensorless vector control method that estimates the rotor speed using stator current. The estimated speed is used as feedback in a vector control system. The conventional MRAS structure has a problem the error output is decreasing as estimated speed error is increasing and the estimation performance is not robust when mutual inductance has been changed. In the proposed method, error output is proportional to estimated speed error. The described technique is less complex, robust to variations of mutual inductance. This new method can achieve much wider bandwidth speed control than that of the conventional MRAS structure.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.640-643
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• 1997

This paper describes speed controller of a induction motor for electric vehicles using PLL and Fuzzy logic. The proposed system is combined precise speed control of PLL and robust, fast speed control of Fuzzy logic. The motor speed is adaptively incremented or decremented toward the PLL locking range by the Fuzzy logic using information of sampled speed errors and then is maintained accurately by PLL. The results of experiment show excellence of proposed system and that the proposed system is appropriates to control the speed of induction motor for electric vehicles.

• 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.

• 한국조명전기설비학회지:조명전기설비
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• 제9권3호
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• pp.88-96
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• 1995

고속 엘리베이터는 높은 안정성과 제어성이 필요하므로 기동, 정지시에 영 속도를 포함한 정밀 구동이 필요하다. 유도전동기의 정밀 구동을 위하여 사용되어온 벡터 제어 기법은 슬립 주파수 제어에 의한 간접 벡터 제어와 계자편향에 의한 직접벡터 제어의 두가지 종류로 분류할 수 있으며, 직접벡터제어의 경우 전동기 제어 변수의 변화에 강건한 반면에 직접 벡터 제어의 경우 비교적 넓은 속도구간에서 제어가 가능하다는 장점을 가지고 있다. 본 논문에서 토크는 직접 벡터기반으로 제어하고, 지속은 간접 벡터 기반으로 제어함으로써 유도전동기의 과도상태 동작과 시동시 영 속도 부근 및 저속 영역에서의 동작이 보다 강건하도록 개선된 직접토크-간접자속(DTIF, Direct Torque Indirect Flux)제어기를 제시하였다. 3상 유도전동기의 구동을 위하여 제안된 시스템의 수행결과는 시뮬레이션과 실험을 통하여 입증하였으며, 영 속도부근과 저속에서 고속으로의 변환과정은 속도응답에 대한 상전압, 상전류 그리고 DC링크 전류를 비교 측정하여 안정하고 강건한 속도변화가 이루어짐을 확인 할 수 있었다.