• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.188-195
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• 2004

This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.27-30
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• 2000

In this paper, we propose a new approach to determination of environment forces acting on a rigid body. To estimate the output of disturbance observer due to internal torque, the disturbance observer output estimator using functional link neural network (FLANN) is designed. It is also shown by simulation results that the precise estimation of contact force is achieved for a 2-link SCARA robot performing position/force control.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.320.1-320
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• 2002

In a hard disk drive (HDD) control system, a state-space controller/observer design is popularly adopted fur its advantages such as effective filtering of position and velocity, use of estimation error to handle servo defects, etc. In this report, a systematic method is proposed to accommodate the transport delay in the plant dynamics into the state estimator. (omitted)

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.289-292
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• 2002

A sensorless control of a PM synchronous motor under the parameter variation is presented. The rotor position is estimated by using the d-axis and q-axis current errors between the real system and motor model of the estimator. The stator resistance is measured at low speeds when the motor changes its rotating direction. The gains in the position estimator are also adapted according to the motor speeds.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.794-803
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• 2016

This paper propose a sensorless control system of IPMSM with a adaptive back-EMF estimator and improved instantaneous reactive power compensator. A saliency-based back-EMF is estimated by using the adaptive algorithm. The estimated back-EMF is inputted to the phase locked loop(PLL) and the improved instantaneous reactive power(IRP) compensator for estimating the position/speed of the rotor and compensating the error components between the estimated and the actual position, respectively. The stability of the proposed system is achieved through Popov's hyper stability criteria. The validity of proposed algorithm is verified by the simulations and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.648-651
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• 1996

Samsung Electronics has developed high performance velocity and position controller for induction motors, and succeeded in mass production for the first time in Korea. Dynamic performance and final control accuracy of the controller are equivalent to those of AC servo motor controller. At present, we adopted the controller as spindle motor drive for Samsung CNC systems, and expect its wide use in industry as general purpose velocity and position controller for induction motor.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.11-14
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• 1996

Samsung Electronics has developed high performance velocity and position controller for induction motors and succeeded in mass production for first time in Lorea. Dynamic performance and final control accuracy of the controller are equivalent to those of AC servo motor controller. At present we adopted the controller as spindle motor drive for Samsung CNC systems and expect its wide use in industry as general purpose velocity and position controller for induction motor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1868-1878
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• 2016

This paper proposes a novel velocity estimator for long-term underwater navigation of autonomous underwater vehicles(AUVs). Provided that an external position fix is not given, a viable goal in designing a underwater navigation algorithm is to reduce the divergence rate of position error only using the sporadic velocity information obtained from Doppler velocity log(DVL). For such case, the performance of underwater navigation eventually depends on accuracy and reliability of external velocity information. This motivates us to devise a velocity estimator which can drastically enhance the navigation performance even when the DVL measurement is unavailable. Incorporating the Gertler-Hagen hydrodynamics model of an AUV with the measurement models of velocity and depth sensors, the velocity estimator design problem is resolved using the extended Kalman filter. Different from the existing methods in which an AUV simulator is regarded as a virtual sensor, our approach is less sensitive to the model uncertainty often encountered in practice. This is because our velocity filter estimates the simulator errors with sensor aids and furthermore compensates these errors based on the indirect feedforward manner. Through the simulations for typical AUV navigation scenarios, the effectiveness of the proposed scheme is demonstrated.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.4
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• pp.266-275
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• 2008

The sensorless speed control technique for BLDC motor using digital IP control is proposed in this paper for advanced speed characteristic which is robust to motor parameters and load variations. The sensorless drive of BLDC motor using terminal voltages is affected by load or speed because it uses analog filters to estimate the rotor position. For this reason, the robust speed controller with the accurate rotor position estimator is needed for sensorless control which is robust to load and insensitive to motor parameters. The constant speed robust to load variation and the stable sensorless control of BLDC motor robust to the increase or decrease of speed with constant load is implemented using digital IP control in this paper. The validity to these is established with experimentation.