• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.4
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• pp.199-205
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• 2012

This paper propose a improved parameter estimations of five-phase squirrel-cage induction motor(IM) for speed control system on field oriented control(FOC). In order to high performance control of ac the motors using a FOC and DTC(direct torque control) algorithm, there are required precise motor parameters for slip calculation, flux observer, controller gain, rotor position and speed estimation, and so on. We are suggest a estimation method of the motor parameters that developing five-phase squirrel-cage IM have a stator of concentrated winding for experimental. There are results of stator winding test, no-load test, locked rotor test, and obtained equivalent circuits using manufactured experimental apparatus. For presenting the superior performance of the speed control system in adapted the parameters, experimental results are presented using a 32-bit fixed point TMS320F2812 DSP with 1.5[KW] IM.

• Journal of Mechanical Science and Technology
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• v.15 no.6
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• pp.720-726
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• 2001

This paper describes a vehicle driving-load estimation method for application to vehicle Intelligent Cruise Control (ICC). Vehicle driving-load consists of aerodynamic force, rolling resistance, and gravitational force due to road slope and is unknown disturbance in a vehicle dynamic model. The vehicle driving-load has been estimated from engine and wheel speed measurements using a vehicle dynamic model a least square method. The estimated driving-load has been used in the adaptation of throttle/brake control law. The performance of the control law has been investigated via both simulation and vehicle tests. The simulation and test results show that the proposed control law can provide satisfactory vehicle-to-vehicle distance control performance for various driving situations.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.614-616
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• 2004

It is waste of time in industrial plant that the PI controller gain tuning. The PI controller has many trial-and-error steps for gain design. This paper proposes the optimum gain design of PI controller using a speed estimation in sensorless vector-control. In this method, a degree of stability and Hurwitz theory are applied and the controller gain is expressed by system parameters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.851-856
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• 1997

This study is on the estimation of the tool temperature for different tool nose radius and cutting conditions in turning. The experiment has been performed in different cutting conditions such as cutting speed, feed rate, and depth of cut for the tool nose radius, 0.4R, 0.8R using SMC workpiece materials. Tool temperature is measured using thermo-couple which is embedded in the insert tip. Using a multiple linear regression method, the tool temperature can be determined as an exponential equation with cutting variables and tool nose diameters for different tool materials. The equations determined in this study show a good correlation for the cutting conditions and can be used for the tool temperature estimation. The result indicates that the tool temperature decreases for ~ncreasing the tool nose radius in general. Also, nose radius hardly influences on the tool temperature compared with cutting speed, feed rate and depth of cut.

• ETRI Journal
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• v.35 no.6
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• pp.949-959
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• 2013

Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real-time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state-of-the-art method to make the real-time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random-forest-based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi-scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.852-857
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• 2010

As the wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is on how to efficiently operate the wind turbines in a wide range of wind speeds. In general, the wind speed is the main factor that impact on the dynamics of wind turbine system. Wind turbine algorithms are thus required to improve the performance of wind speed measurements. However, the accurate measurement of the effective wind speed using wind gauge and similar sensors is difficult such that control systems are needed for wind speed estimation using various techniques. Therefore, this research suggests the Maximum Power Point Tracking (MPPT) method for tracking the wind speed based on neural networks. Design experiments were carried out in laboratory environment to validate the application of the proposed method.

• The KSFM Journal of Fluid Machinery
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• v.14 no.1
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• pp.5-10
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• 2011

MTG(Micro turbine generator) operating at 400,000 rpm is under development and the impact test rig to measure the dynamic stiffness and damping coefficient of air foil bearing for high speed rotor is presented in this study. The stiffness and damping coefficient of air foil bearing depending on the rotational speed can be measured easily and effectively by using the simple configuration of impact test rig which is composed of air gun, gap sensors and high speed motor. The estimation results of stiffness and dampling coefficient using least square estimation method is presented as well.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2094-2096
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• 1998

In this paper, a new speed estimation method using neural networks is proposed and speed sensorless vector control is realized with the estimated speed. The effectiveness and the usefulness of the proposed algorithms are thoroughly verified with the experiments on the fully-digitalized 2.2kW induction motor drive systems.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.163-165
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• 2006

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK amd dSPACE DSl104 R&D board. The estimation of rotor flux linkage and rotor speed is carried out using model reference adaptive system(MRAS) method. Estimated rotor speed is used to speed controller of induction motor. Simulation results are presented to confirm speed sensorless vector control algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.