• Proceedings of the KIEE Conference
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• 2004.07e
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• pp.33-36
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• 2004

In this paper, a new estimation algorithm for the rotor speed for SRM drives is described. The algorithm is implemented by the sliding mode observer. The stability and robustness of the sliding observer for the parameter variations of the SRM are proved by variable structure control theory. Variable speed control of the SRM is accomplished by the estimated speed. Experiment results verify that the sliding mode observer is able to estimate the speed.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.161-164
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• 2005

In this paper, a new estimation algorithm for the rotor speed for SRM drives is described. The algorithm is implemented by the binary observer. The stability and robustness of the binary observer for the parameter variations of the SRM are proved by variable structure control theory. Variable speed control of the SRM is accomplished by the estimated speed. Experiment results verify that the binary observer is able to estimate the speed.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.101-106
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• 2020

In order to smoothly control the speed of the induction motor, it is necessary to obtain the required rotor speed information. In order to obtain the speed information, it must be obtained using a sensor, but it can also be obtained using an appropriate algorithm without using a sensor. In order to obtain speed information, a system was designed using a model reference adaptive system (MARS). Indirect vector control, one of the speed control methods of induction motors, was calculated from the motor current and rotor parameter values. The method of obtaining the position information of the magnetic flux by combining the slip frequency with the rotor speed was used. It is possible to simply perform instantaneous current control in a wide speed range without actual magnetic flux information, and has the advantage that the structure of the controller is simple. Therefore, in this paper, the control system was constructed based on the indirect vector control method, and the speed control system of the induction motor was developed by estimating the required rotor speed information as an intelligent algorithm developed without using it as a sensor.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.243-250
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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 how to efficiently operate the wind turbines in a wide range of wind speeds. Compared to fixed speed turbines, variable speed wind turbines feature higher energy yields, lower component stress and fewer grid connection power peaks. Generally, measurement of wind speed is required for the control of variable speed wind turbine system. However, wind speed measured by anemometers is not accurate owing to various reasons. In this work, a new control algorithm for variable speed wind turbine system based on Kalman filter which can be used for the estimation of wind speed and artificial neural network which can generate optimum rotor speed is proposed. Also, to verify the feasibility of the proposed scheme, various simulation studies are carried out by using Simulink in Matlab.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.93-102
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• 2014

Recently the interest in permanent magnet alternating motor using for electric compressor become great. Especially the research on Interior Permanent Magnet Motor has been doing actively for its advantages in the energy density and the efficiency. In order to control the output of motor to the desired value, the current control or speed control of motor are required. The accurate detection of rotor position and speed information are necessary for the control of motor. In general, the encoder, hall sensor, and resolver are used to obtain the information of motor position and speed and the speed detection algorithm, M/T method, is applied. However, the M/T method causes the error depending on rotor speed. Therefore, this M/T speed detection method is not perfect. In this paper, it is proposed that the PI control with a 1st transfer function and the integration element between velocity and position are composed in series and this feeds back to the reference value of position angle. The proposed algorithm is a function of the integral elements 2nd term, speed element, is used as an output. Thus, it is possible to detect the correct speed by configuring like the mechanical structure similarly. The proposed algorithm is verified by using PSIM DLL and is applied to the BLAC motor drive. And also it is confirmed that this system estimates the accurate speed regardless of rotor speed changes. As a example, the experimental results and simulations shows that the proposed method is very effective.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.115-125
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• 2016

PURPOSES : This study proposes a methodology to collect data necessary for microlevel emission estimation, such as second-by-second speeds and road grades, and to accordingly estimate emissions. METHODS : To ease data collection for microlevel emission estimation, a vehicle equipped with speed- and location-recording instruments as well as equipment for measuring road geometry was used. As a case study, this vehicle and the proposed methodology were used on a 10-km-long highway in Yongin City, Korea. Emissions from the vehicle during driving were estimated in various microscale driving conditions. RESULTS : Differences in the estimated emission under different microscale driving conditions cannot be ignored. Compared with the estimations obtained when second-by-second data were not considered, CO and NOx emissions were more than threefold higher when considering second-by-second speed; similarly, CO and NOx emission estimations were higher by approximately 10% and 3%, respectively, when considering second-by-second road grade. CONCLUSIONS : The proposed method can estimate vehicle emissions under real-world driving conditions in such applications as road design and traffic policy assessments.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.659-666
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• 2021

With the continuous development of deep learning, human behavior recognition algorithms have achieved good results. However, in a multi-person recognition environment, the complex behavior environment poses a great challenge to the efficiency of recognition. To this end, this paper proposes a multi-person pose estimation model. First of all, the human detectors in the top-down framework mostly use the two-stage target detection model, which runs slow down. The single-stage YOLOv3 target detection model is used to effectively improve the running speed and the generalization of the model. Depth separable convolution, which further improves the speed of target detection and improves the model's ability to extract target proposed regions; Secondly, based on the feature pyramid network combined with context semantic information in the pose estimation model, the OHEM algorithm is used to solve difficult key point detection problems, and the accuracy of multi-person pose estimation is improved; Finally, the Euclidean distance is used to calculate the spatial distance between key points, to determine the similarity of postures in the frame, and to eliminate redundant postures.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.327-333
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• 2015

Wind turbines, in the case of less than rated wind speed, is controlled to achieve maximum power. MPC(Maximun Power Control) method, by controlling the rotational speed of the generator, is a method to achieve maximum power but should know the wind speed. However, for several reasons, there have been proposed methods of estimating the wind speed rather than measuring wind speed. TSR(Tip Speed Ratio) is needed to know to estimate the wind speed. However, a complex interaction formula has to be solved to find a TSR. Therefore, many methods have been suggested to solve a complex interaction formula. In this paper, the new method has been proposed to simplify the complicated interaction formula by using the regression method. Matlab/Simulink is used to simulate and to verify the proposed method.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.231-237
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• 2018

This paper investigates the impact of the channel variations and channel estimation errors on the error performance of convolutional coded STBC systems. We consider the orthogonal Almouti STBC and the quasi-orthogonal Jafarkhani STBC, and the error performance of the convolutional coded STBC system is investigated according to the channel variation and channel estimation error via numerical simulations. Simulation results show that, if the channel variation speed is slow, time diversity effects improve the error performance compared to the static-channel cases. However, if the channel variation speed is fast, unlike ZF or MMSE detection, the conventional STBC detection has the significant performance degradation especially with the quasi-orthogonal Jafarkhani STBC. Further, the error performance of the system is significantly degraded as the channel estimation errors become stronger, regardless of the detection scheme and channel variation speed.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.858-863
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• 2010

In order to enhance encoding speed in dynamic image encoding using H.264/AVC, reducing the time for motion estimation which takes a large portion of the processing time is very important. An approach using graphics processing unit(GPU) as a coprocessor to assist the central processing unit(CPU) in computing massive data, will be a way to reduce the processing time. In this paper, we present an efficient block-level parallel algorithm for the motion estimation(ME) on a computer unified device architecture(CUDA) platform developed in general-purpose computation on GPU. Experiments are carried out to verify the effectiveness of the proposed algorithm.