• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2189-2196
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• 2016

This paper proposes a new finite control set-model predictive control (FCS-MPC) method for induction motors. In the method, the reference state that satisfies the given torque and rotor flux requirements is derived. Cost indices for the FCS-MPC are defined using the state tracking error, and a linear matrix inequality is formulated to obtain a proper weighting matrix for the state tracking error. The on-line procedure of the proposed FCS-MPC comprises of two steps: select the output voltage vector of the two level inverter minimizing the cost index and compute the optimal modulation factor of the minimizing output voltage vector in order to reduce the state tracking error and torque ripple. The steady state tracking error is removed by using an integrator to adjust the reference state. The simulation and experimental results demonstrated that the proposed FCS-MPC shows good torque, rotor flux control performances at different rotating speeds.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.51-58
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• 2006

To compensate for the motion errors in hydrostatic tables, a method to actively control the clearance of a bearing corresponding to the amount of error using actively controlled capillaries is introduced in this paper. The design method for an actively controlled capillary that considers the output rate of a piezo actuator and the amount of error that must be corrected is described. The basic characteristics of such a system were tested, such as the maximum controllable range of the error, micro-step response, and available dynamic bandwidth when the capillary was installed in a hydrostatic table. The tests demonstrated that the maximum controllable range was $2.4\;{\mu}m$, the resolution was 27 nm, and the frequency bandwidth was 5.5 Hz. Simultaneous compensation of the linear and angular motion errors using two actively controlled capillaries was also performed for a hydrostatic table driven by a ballscrew and a DC servomotor. An iterative compensation method was applied to improve the compensation characteristics. Experimental results showed that the linear and angular motion errors were improved to $0.12{\mu}m$ and 0.20 arcsec, which were about $1/15^{th}$ and $1/6^{th}$ of the initial motion errors, respectively. These results confirmed that the proposed compensation method improves the motion accuracy of hydrostatic tables very effectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2028-2037
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• 2009

This paper presents the simulator for dynamic modeling of a MT(micro turbine) during start-up period. The simulator is implemented by modeling a dynamic power of main components of a MT including compressor, combustor and turbine. A modeling for a MT under steady state operation can be accurately built from thermodynamics analysis. But dynamic modeling during start-up period is very difficult because efficiency of main components is very low and the designed value has big error and nonlinear characteristics during start-up. In this paper, new method without using thermodynamics analysis during start-up is proposed for the simulator. The power models of main components are derived from analysis of the experimental operation data by test motoring using a electric starter under constant power output. The simulator is developed using MATLAB/Simulink. For constant power output control, sensorless vector inverter is designed and algorithms for starting from stall and method for controling a output power are proposed. The performance of developed simulator is verified by comparing experimental and simulation start-up results.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.523-525
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• 2004

Over the last few years, the control of bipedal robot has been considered a promising research field in the community of robotics. But the problems we encounter make the control of a bipedal robot a hard task. The complicated link connection of the bipedal robot makes it impossible to achieve its exact model. In addition, the joint velocity is needed to accomplish good control performance. In this paper a control method using ANFIS as an system approximator is purposed. First a model biped robot of a biped robot with switching leg influence is presented. Unlike classical method, ANFIS approximation error estimator is inserted in the system for tuning the ANFIS. In the entire system, only ANFIS is used to approximate the uncertain system. ANFIS tuning rule is given combining the observation error, control error and ANFIS approximation error. But this needs velocity information which is not available. So a practical method is newly presented. Finally, computer simulation results is presented to show this control method has good position tracking performance and robustness without need for leg switching acknowledgement.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.1003-1010
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• 2008

In this paper, we propose the new method to decrease the navigation error by measurement time synchronization error in RLG Trapping signal processing. There are two methods to eliminate the dither motion in RLG. One is the stripping signal processing method. Another is the trapping signal processing method. This two methods have various error sources in measurement output. We perform the error modelling and analysis for the measurement time synchronization error between angular rate from RLG and acceleration from accelerometer in the trapping signal processing method. And we verify the navigation performance through simulation and experiment. Results of simulation and experiment show that the proposed method is very effective in decreasing the navigation error.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.1 s.24
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• pp.89-98
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• 2006

This paper describes signal attenuation characteristics as splicing the output on LVDT for stability and reliability of switching mechanism, which is developed to use common signal between FLCC and EDFLCC, on T-50 aircraft. The method of test is classified a Pspice simulation and an actual hardware evaluation. The difference of error margin for two methods is 10times, the latter higher. The result in this experiment shows that the signal attenuation as splicing the output on LVDT doesn't affect and the static error margin is 53% for develope the EDFLCC.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1730-1731
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• 2007

In this paper, we present a direct adaptive control method using neural networks for the control of nonlinear systems. The weights of neural networks are trained by an adaptive backpropagation algorithm based on Lyapunov stability theory. We develop the parameter update-laws using the neural network input and the error between the desired output and the output of nonlinear plant to update the weights of a neural network in the sense that Lyapunove stability theory. Beside the output tracking error is asymptotically converged to zero.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1685-1690
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• 2014

This paper proposes a novel method to compensate for the measurement errors in detecting phase currents for vector-controlled inverter in real-time. The output torque equations for 3-phase induction motor are derived in terms of offset error and transducing gain error in current measurement circuits, and the equations shows that motor output torque has many ripples due to current measurement errors. Especially, if the proposed method is applied to vector-controlled inverter, the torque ripple by transducing gain error can be reduced in real-time at running state of motor. To verify the proposed method, it was applied to vector-controlled inverter for 3-phase induction motor of 200[W] and computer simulation and experimentation were carried out.

• Journal of Magnetics
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• v.18 no.4
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• pp.454-459
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• 2013

This paper deals with an optimal angle error reduction method of magnetic position sensor using hall effect elements. The angle detection simulation for the magnetic position sensor is performed by 3 dimensional finite element method and Taguchi method, one of the design of experiments. The magnetic position sensor is required to generate ideal sine and cosine waveforms from its hall effect elements according to rotation angle for precise angle information. However, the output signals are easy to include harmonics due to uneven magnetic field distribution from permanent magnet in the air-gap in the vicinity of hall effect elements. For the Taguchi method, three design parameters related to position of hall effect elements and shape of back yoke are selected. The characteristics of optimal magnetic position sensor are compared with those of original one in terms of simulation as well as experiment. Finally, the performances of the motor adopting original model and optimal model are represented for the purpose of verification of motor performance due to signals from magnetic position sensor.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.525-526
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• 2008

For measuring nonlinear Vehicle Modeling based on 7-Depth Sensor, the neural networks are proposed m adaptive and in realtime. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models.