• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1013-1016
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• 2000

In this study, the estimate speed of rotor in the induction motor with Model Reference Adaptive control System (MARC) principle and to study that vector control system feedbacks speed estimated to speed control system and its result is as follows; Considering with explanation an influence of speed estimation mechanism depend on error about the second resistance size established, it estimates the deviation of the second resistance establishment and exhibits a compensation method, what is more, it designs a reparation program using the fuzzy algorithm and testifies the result with the computer simulation. And besides, it composes the load torque estimation and estimates the load torque, as the result, feedback-compensating the result of estimation, it improves the efficiency. In consequence, it makes a good result for more powerful vector control system about the outside trouble.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.319.1-319
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• 2002

A frequency-domain PES estimation and its prediction method are proposed for the tightly-coupled servo/mechanical design of high-TPI HDD system above 100kTPI. The major two disturbance energies which are related with mechanical vibrations inside of HDD are used to predict the drive-level PES, while considering closed-loop servo dynamics. One is the torque disturbance which mainly comes from aerodynamic excitation of HSA system and the other is the displacement disturbance from disk-spindle dynamics. (omitted)

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.3
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• pp.372-378
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• 2016

Clutch torque control is the key to the ride comfort improvement of a vehicle equipped with AMT (automated manual transmission). For such control, the torque transfer starting point, known as the "kiss point," should be indicated or at least estimated to compensate for the clutch torque. The kiss point changes due to wear, high temperature, and fatigue; as such, it should be estimated while the vehicle is being driven. In this study, the method of kiss point active estimation for an AMT vehicle with a dry-type clutch was devised. The kiss point is learned while the engine is in an idle state and while the transmission is at a neutral gear position. It is determined when the input shaft of the transmission starts to rotate by slowly engaging the clutch. The noise of the shaft speed signal during the slow engagement process is filtered for accurate control. The kiss point estimation at various clutch engagement speeds was analyzed via a vehicle test.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.346-350
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• 2001

PMSM drives are widely used in the industrial and residential applications because of high efficiency, high power density and high performance. For better performance of PMSM, however, torque ripples should be reduced. This paper investigates a reduction of torque ripple due to the unsinusoidal flux linkage produced by the shapes of stator slot and magnetic pole. To minimize torque ripple, a simple flux estimator is proposed. This method interatively compensates the distributed flux linkage from an error between the measured and estimated currents. The proposed algorithm is verified through simulation.

• Journal of Power Electronics
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• v.9 no.4
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• pp.582-592
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• 2009

This paper proposes a new speed sensorless direct torque and flux controlled interior permanent magnet synchronous motor (IPMSM) drive. Closed-loop control of both the torque and stator flux linkage are achieved by using two proportional-integral (PI) controllers. The reference voltage vectors are generated by a SVM unit. The drive uses an adaptive sliding mode observer for joint stator flux and rotor speed estimation. Global asymptotic stability of the observer is achieved via Lyapunov analysis. At low speeds, the observer is combined with the high frequency signal injection technique for stable operation down to standstill. Hence, the sensorless drive is capable of exhibiting high dynamic and steady-state performances over a wide speed range. The operating range of the direct torque and flux controlled (DTFC) drive is extended into the high speed region by incorporating field weakening. Experimental results confirm the effectiveness of the proposed method.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.251-260
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• 2015

The main purpose of this paper is to describe a DTC (direct torque control) method for four-switch brushless dc motor (BLDCM) drive. In the method, a novel voltage space vector modulation scheme, an optimal switching table, and a flux observation method are proposed. Eight voltage vectors are summarized, which are selected to control BLDCM in SVPWM pattern, and an optimal switching table is proposed to improve the torque distortion caused by midpoint current of the split capacitors. Unlike conventional flux observers, this observer does not require speed adaptation and is not susceptible to speed estimation errors, especially, at low speed. Global asymptotic stability of the flux observer is guaranteed by the Lyapunov stability analysis. DC-offset effects are mitigated by introducing a PI component in the observer gains. This method alleviates the undesired current and torque distortion which is caused by uncontrollable phase. The correctness and feasibility of the method are proved by simulation and experimental results.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.9
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• pp.915-921
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• 2012

In this study, we propose a new method for estimating the IMEP using difference pressure, which is the pressure difference between the cylinder pressure and the motoring pressure. The estimated IMEP, denoted as $IMEP_{diff}$, optimizes the theoretical IMEP calculation range based on the fact that the difference pressure exists between the start and the end of combustion. $IMEP_{diff}$ is verified to have a high linear correlation with IMEP with $R^2$ of 0.9955. The proposed method can estimate the IMEP with 21% of the cylinder pressure data and 31% of the calculation effort compared to the theoretical IMEP calculation method, and therefore, it has great potential for real-time implementations. The estimation and control performance of $IMEP_{diff}$ is validated by engine experiments, and by controlling $IMEP_{diff}$, the torque variation between the cylinders was reduced.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.6
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• pp.670-677
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• 2011

This study is to estimate the joint torques without torque sensor using the EMG (Electromyogram) signal of agonist/antagonist muscle with Neural Network Back Propagation Algorithm during the elbow motion. Command Signal can be guessed by EMG signal. But it cannot calculate the joint torque. There are many kinds of field utilizing Back Propagation Learning Method. It is generally used as a virtual sensor estimated physical information in the system functioning through the sensor. In this study applied the algorithm to obtain the virtual senor values estimated joint torque. During various elbow movement (Biceps isometric contraction, Biceps/Triceps Concentric Contraction (isotonic), Biceps/Triceps Concentric Contraction/Eccentric Contraction (isokinetic)), exact joint torque was measured by KINCOM equipment. It is input to the (BP)algorithm with EMG signal simultaneously and have trained in a variety of situations. As a result, Only using the EMG sensor, this study distinguished a variety of elbow motion and verified a virtual torque value which is approximately(about 90%) the same as joint torque measured by KINCOM equipment.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.133-138
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• 1993

This paper presents neural network based position estimation method in slippery environment as an approach to solve one of problems which are engaged in dead reckoning method. Position estimator is composed of slip detector and linear velocity estimator. Both of them are based on the fact that dynamic characteristic of mobile robot in slippery environment is different from the case without slip. To find out the dynamic relation among driving torque, angular acceleration of driving wheel and linear acceleration of mobile robot, accelerometer is used for measuring acceleration of mobile robot and neural network is used for dynamic system identifier in slippery environment.