• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.108-121
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• 2019

This paper presents the study results on the design of the correction filter to improve the azimuth error estimation of the high-speed guided missile launched from the warship after the transfer alignment. We theoretically proved that the transfer alignment performance is determined by the accuracy of the marine inertial navigation system and the observability of the attitude error state variable in the transfer alignment filter, and that most of navigation errors in high-speed guided missile are caused by azimuth error. In order to improve the azimuth estimation performance of the correction filter, the multiple adaptive estimation method and the adaptive filters adapting the measurement noise covariance or the process noise covariance are proposed. The azimuth estimation performance of the proposed adaptive filter and the existing Kalman filter are compared and analyzed each other for 8 different transfer alignment accuracy cases. As a result of comparison and analysis, it was confirmed that the adaptive filter adapting the process noise covariance has the best azimuth estimation performance. These results can be applied to the design of correction filters for high-speed guided missile.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and 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. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.326-331
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• 1990

In the vector-controlled induction machine drive, mechanical sensors restrict the wide applications of high performance AC drives. So in resent years, many papers have been presented which doesn't need mechanical sensors, named by sensorless vector control. But sensorless control has a few serious problem, one of which Is poor speed estimation in case of incorrect rotor resistance (Rr) information. This paper describes the stator flux orientation speed control strategy with the speed estimation algorithm. and the method of adapting Rr change due to thermal heating. By proposed method. We can acquire precise speed estimation and higher performance.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.160-164
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• 2007

MRAS observer, which is based on adaptive control theory, estimates speed and position by using optimal observer gains on the basis of Lyapunov stability theory. However, in case of MRAS theory, position estimation error is in existence because of non-linearity for inductance variation and limit cycles for position estimation. The adaptive sliding observer based on the variable structure control theory estimates the speed and position for zero of estimation error by using the sliding surface equal to the error between speed and position estimation. The binary observer estimates the rotor speed and rotor flux with alleviation of the high-frequency chattering, and retains the benefits achieved in the conventional sliding observer, such as robustness to parameter and disturbance variations. The speed and position sensorless control of SRM under the load and inductance variation is verified by the experimental results.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.544-548
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• 1999

Using Observer, on the sensorless vector control system is a novel techniques for modern induction motor control. In this paper, a speed estimation algorithm of an induction motor using an extended kalman filter was proposed. Extended kalman filter can solve the problem, that have steady state error of estimated speed in flux and slip estimation method. The extended Kalman filter is employed to identify the speed of an induction motor and rotor flux based on the measured quantities such as stator current and DC link voltage. In order to confirming above proposal, computer simulation carried out using Matlab Simulink and show the effectiveness of the control drives for induction motor speed estimation.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.298-303
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• 1998

In the speed sensorless control of the induction motor, the machine parameters (especially the secondary resistance R2) have a strong influence to the speed estimation. It is known that the simultaneous estimation of the speed and R2 is impossible in the slip frequency type vector control, because the secondary flux is constant. But the secondary flux is not always constant in the speed transient state. In this paper the R2 estimation in the transient state without adding any additional signal to the stator current is proposed. This algorithm uses the least mean square algorithm and the adaptive algorithm, and it is possible to estimate the R2 exactly. This algorithm is verified by the digital simulations and the experiments.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.552-561
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• 2004

This paper is concerned with a new speed sensorless induction motor scheme which can be successfully applied to at any speed including even zero speed. The proposed method is robust against rotor resistance variations. In addition, simultaneous on-line estimations of speed and rotor resistance are realized based on a feedforward type torque control approach. The rotor flux with a low frequency sinusoidal waveform has been utilized to help the simultaneous estimation for both speed and rotor resistance. The control scheme has no current minor loop to determine voltage references. Since the proposed estimation does not depend on any derivative terms of currents and stator voltages, it offers a good performance at extremely low speed region for sensorless induction motor. Furthermore, the proposed control is simply using motor parameters and stator currents without determining any PI gains for current feedback and any signal injection for the rotor resistance estimation. Finally, both simulation and experimental results are given to show the effectiveness of this method.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.58-65
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• 2003

Vehicle acceleration data from an accelerometer and wheel speed data from standard, 50-tooth antilock braking system wheel speed sensors are used to estimate the absolute longitudinal speed of a vehicle. We develop the four velocity estimation algorithms. And we compare experimental results with the Butterworth filtered speed from the fifth wheel and find that it is possible to estimate absolute longitudinal vehicle speed during a hard braking maneuver lasting three seconds.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1104-1109
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• 2010

This paper deals with the attitude control of an underactuated spacecraft that has fewer than three actuators. Even though such spacecrafts are known as uncontrollable, restricted missions are possible with controlling two-axis attitude angles. A variable speed control moment gyroscope is considered as an actuator. It is a kind of momentum exchange device and it shows highly nonlinear dynamical properties. Speed commands are generated by kinematic equations represented by Euler angles. A control law, that is designed to make a spacecraft follow the speed commands, is derived by the backstepping method. Angular speeds are estimated from the attitude measurements. Several estimation methods have been compared.