• Journal of Power Electronics
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• v.16 no.4
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• pp.1375-1386
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• 2016

To decouple the secondary saliencies in sensorless permanent magnet synchronous machine (PMSM) drives, a repetitive control (RC) in the angle domain is proposed. In this paper, the inductance model of a concentrated windings surface-mounted PMSM (cwSPMSM) with strong secondary saliencies is developed. Due to the secondary saliencies, the estimated position contains harmonic disturbances that are periodic relative to the angular position. Through a transformation from the time domain to the angle domain, these varying frequency disturbances can be treated as constant periodic disturbances. The proposed angle-domain RC is plugged into an existing phase-locked loop (PLL) and utilizes the error of the PLL to generate signals to suppress these periodic disturbances. A stability analysis and parameter design guidelines of the RC are addressed in detail. Finally, the proposed method is carried out on a cwSPMSM drive test-bench. The effectiveness and accuracy are verified by experimental results.

• Journal of Power Electronics
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• v.10 no.5
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• pp.485-490
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• 2010

Sensorless control methods are generally used in motor control for home-appliances because of the material cost and manufactureing standard restrictions. The current model-based control algorithm is mainly used for PMSM sensorless control in the home-appliance industry. In this control method, the rotor position is estimated by using the d-axis and q-axis current errors between the real system and a motor model of the position estimator. As a result, the accuracy of the motor model parameters are critical in this control method. A mismatch of the PMSM parameters affects the speed and torque in low speed, steadystate responses. Rotor position errors are mainly caused by a mismatch of the stator resistance. In this paper, a stator resistance compensation algorithm is proposed to improve sensorless control performance. This algorithm is easy to implement and does not require a modification of the motor model or any special interruptions of the controller. The effectiveness of the proposed algorithm is verified through experimental results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.12
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• Smart Structures and Systems
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• v.3 no.3
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• pp.245-261
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• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.132-139
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• 2008

The blade vibration problem of bladed disk is the most critical subject to consider since it directly affects the stable performance of the engine as well as life of the engine. Especially, due to complicated vibration pattern of the bladed disk, more effort was required for vibration analysis and test. The research of measuring the vibration of the bladed disk, using NSMS(Non-intrusive stress measurement) instead of Aeromechanics testing method requiring slip ring or telemetry system with strain gauge, was successful. These testing can report the actual stresses seen on the blades; detect synchronous resonances that are the source of high cycle fatigue (HCF) in blades; measure individual blade mis-tuning and coupled resonances in bladed disks. In order to minimize the error being created due to heat expansion, the tip timing sensor is installed parallel to the blade trailing edge, yielding optimal result. Also, when working on finite element analysis, the whole bladed disk has gone through three-dimensional analysis, evaluating the family mode. The result of the analysis matched well with the test result.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.282-289
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• 2005

This paper proposes a fuzzy neural network controller based on the vector control for interior permanent magnet synchronous motor(IPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability This paper does not oかy presents speed control of IPMSM using neuro-fuzzy control(NFC) but also 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. Thus, it is presented the theoretical analysis as well as the analysis results to verify the effectiveness of the proposed method in this paper.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.226-228
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• 2002

This paper presents a new control approach for designing a coordinated controller for static VAR compensator system. A SVC constructed by a Fixed Capacitor and a Thyristor Controlled Reactor is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. A design of linear quadratic controller based on optimal controller depends on choosing weighting matrices. A coordinated optimal controller is achieved by minimizing a quadratic performance index using dynamic programming techniques. The selection of weighting matrices is usually carried out by trial and error which is not a trivial problem. We proposed a efficient method using GA of finding weighting matrices for optimal control law. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.505-508
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• 1997

In this paper, an auto-tuning method for fuzzy controller based on the neural network is presented. The backpropagated error of neural emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and used for speed control of induction motor. For the torque control method, an indirect vector control scheme with slip calculation is used because of its stable characteristics regardless of speed. Motor input current is regulated by a current controlled voltage source PWM inverter using space voltage vector technique. Also, the scheme of current control fuzzy controller is synchronous reference frame with decoupling term. DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzz. control algorithm. An IPM is used to simplify hardware design.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.530-543
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• 2013

This paper describes a control scheme of speed sensorless fuzzy direct torque control (FDTC) of permanent magnet synchronous motor for electric vehicle (EV). Electric vehicle requires fast torque response and high efficiency of the drive. Speed sensorless FDTC In-wheel PMSM drives without mechanical speed sensors at the motor shaft have the attractions of low cost, quick response and high reliability in electric vehicle application. This paper presents a new approach to estimate the speed of in-wheel electrical vehicles based on Model Reference Adaptive System (MRAS). The direct torque control suffers in low speeds due to the effect of changes in stator resistance on the flux measurements. To improve the system performance at low speeds, a PI-fuzzy resistance estimator is proposed to eliminate the error due to changes in stator resistance. High performance sensorless drive of the in-wheel motor based on MRAS with on line stator resistance tuning is established for four motorized wheels electric vehicle and the whole system is simulated by matalb/simulink. The simulation results show the effectiveness of the new control strategy. This proposed control strategy is extensively used in electric vehicle application.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.280-286
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• 1998

This paper proposes a novel method to reduce the torque ripple due to the non-ideality of the current sensing parts in vector-controlled inverter-fed AC motor drive systems. For PMSM(Permanent Magnet Synchronous Motor), motor output torque equations are derived in terms of their offset voltages and different voltage transducing gains. And the effects of phase current errors on motor torque are analyzed for both salient PMSM and non-salient PMSM. The proposed method can eliminate the torque ripple by nulling the offset voltages and setting the voltage transducing gains to the same value. To verify the proposed method, digital simulations are carried out for non-salient PMSM.