• Proceedings of the KIEE Conference
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• summer
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• pp.1291-1293
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• 2004

The control method of programmable dynamometer for overall test of machine is to load the reference torque which is computed from torque transducer into motor under test. But the torque information detected from torque transducer have a lot of noise when the load torque of meter is a small quantity or changing. Thus, torque transducer must have a low pass filter to detect a definite torque information. But The torque delay generated by filter with torque transducer occur a torque trouble for moter torque of programmable dynamometer. Therefore, this kind of system could not perform dynamic and nonlinear load. In this paper, the control method using the load torque observer without a measure for torque transducer is proposed. The proposed system improved the problem of the torque measuring delay with torque transducer, and the load torque is estimated by the minimal order state observer based on the torque component of the vector control induction meter. Therefore, the torque controller is not affected by a load torque disturbance.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.252-260
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• 1997

In this paper, a friction compensation method using a disturbance observer is proposed for an impedance control of pneumatic manipulator. It is assumed that the generated torque by a pneumatic actuator can be estimated based on the pressure signals and the discharge volume. In order to improve the dynamic characteristics of the pneumatic actuator driven by meter out method, we construct the inner torque control system by feeding back the generated torque. In order to reduce the influence of disturbances comprising friction torque and parameter variations of plant, the impedance control system is constructed with a disturbance observer which estimates the disturbances based on the generated torque of pneumatic actuator, the angular velocity and the reaction torque. From some experiments, it is confirmed that the proposed control system is effective to improve the robustness for the friction torque in the impedance control of a pneumatic manipulator.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1995.10a
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• pp.96-100
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• 1995

In this paper an induction motor control using fuzzy controller and neural network adptive observer is studied. The proposed observer which comprises neural network flux observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subjected to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations

• Journal of Power Electronics
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• v.13 no.6
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• pp.975-984
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• 2013

This paper proposes a robust optimal nonlinear control with an observer to reject the offset errors of position tracking for surface mounted permanent magnet synchronous motors. We provide the control method to reject offset errors and load torque for designing field oriented control (FOC) based the alternating current (AC) frame. The proposed method consists of a torque generator, a commutation scheme, an electrical controller, and a load torque observer. The mechanical controller is designed to compensate for load torque and the offset error and generate the desired torque. The commutation scheme is proposed to create the desired currents for the desired torque. The electrical controller is developed to guarantee the desired currents. The observer is designed to estimate both the velocity and the load torque. In order to obtain the robustness to parameter uncertainties and a gain tuning guide, the linear quadratic regulator method is applied to the proposed method. The closed-loop stability is proven. A detailed process for the FOC design and an analysis of the control methods based on the AC frame are presented. The performance of the proposed method was validated via experiments. The proposed method obtains the FOC based on the AC frame. Furthermore, the position tracking performance of the proposed method is superior to that of the conventional method.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.2
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• pp.99-106
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• 1998

This paper proposed a speed control system for induction motors robust to variations in torque and parameters by feedforward compensating the current portion of load torque, adding a load torque observer to the conventional PI controller in the indirect vector controlled induction motor system. Computer simulations and exeperimental works using the proposed control confirm that the transient response for the variation of the reference speed and load torque becomes improved, compared with the conventional PI controled method.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.138-143
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• 1999

A new control method for the precision robust position control of a brushless DC(BLDC) motor for direct drive m motor(BLDDM) system using the asymptotically stable adaptive load torque observer is presented. A precision position c control is obtained for the BLDD motor system appro성mately linearized using the fieldlongrightarroworientation method. Many of t these motor systems have BLDD motor to obtain no backlashes. On the other hand, it has disadvantages such as the h high cost and more complex controller caused by the nonlinear characteristics. And the load torque disturbance is d directly affected to a motor shaft. To r밍ect this problem, stability analysis is calTied out using Lyapunov stability t theorem. Using this results, the stability is proved and load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent CUlTent having the fast response.

• Journal of Power Electronics
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• v.10 no.5
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• pp.498-504
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• 2010

The output power fluctuations of renewable energy power plants such as wind turbine generators and photovoltaic systems result in frequency deviations and terminal voltage fluctuations. Furthermore, these power fluctuations also affect the turbine shaftings of diesel generators and gas-turbine generators which are the main power generation systems on isolated islands. Therefore, it is important to achieve torsional torque suppression. Since the measurement of torsional torque is technically difficult, and there is an uncertainty in the mechanical constants of the shaft torsional system. This paper presents an estimation system that estimates torsional torque by using a developed $H_{\infty}$ observer. In addition to the above functions, the proposed shaft torque observer incorporates a parameter identification system that aims to improve the estimation accuracy. The simulation results validate the effectiveness of the proposed $H_{\infty}$ observer and the parameter identification.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.92-95
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• 2001

This study presents neural load disturbance observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM fellows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.177-181
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• 1997

In the speed control system of motors using the low resolution rotary encoder, the period of encoder pulse becomes longer than the sampling time for speed control in the range of very low speed. Therefore, it is difficult to obtain accurate speed information. In this paper, the speed estimating method at the very low speed region using reduced order torque observer, which has been widely used, is examined. The results of simulation show that the characteristics of the speed control at the very low speed region is improved by using the reduced order torque observer.