• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.148-154
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• 2014

This paper describes problems of the sensorless starting of horizontal axis washing machines with direct drive and suggests solution, which was experimentally verified. Horizontal axis washing machines have very difficult conditions for the drive starting, especially at full load. Inertia of the tub and water, torque from the laundry make load torque at starting higher than rated one and sometimes even higher than the maximum torque of the motor, which makes sensorless starting extremely challenging task. This paper suggests modified open-loop starting, where control system is closed shortly after beginning at low speed and rotates the drum until laundry restructuring. To ensure proper work of the sensorless algorithm at low speed additional measures for increasing of the estimation algorithm performance have been taken. These measures include special algorithm for the drive parameters estimation, which has been developed and verified by the experimental results.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.421-424
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• 1990

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.95-101
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• 2015

To accurately extract absolute distance information from a self-mixing interferometry (SMI) signal, in this paper we propose an approach based on a particle swarm optimization (PSO) algorithm instead of frequency estimation for absolute distance. The algorithm is utilized to search for the global minimum of the fitness function that is established from the self-mixing signal to find out the actual distance. A resolution superior to $25{\mu}m$ in the range from 3 to 20 cm is obtained by experimental measurement, and the results demonstrate the superiority of the proposed approach in comparison with interpolated FFT. The influence of different external feedback strength parameters and different inertia weights in the algorithm is discussed as well.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.97.4-97
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• 2002

1. Introduction Pose estimation of a three dimensional object has been studied in robot vision area, and it is needed in a number of industrial applications such as process monitoring and control, assembly and PCB inspection. In this research, we propose a new pose estimation method based on principal axes analysis. Here, it is assumed that the locations of x-ray source and the image plane are predetermined and the object geometry is known. To this end, we define a dispersion matrix of an object, which is a discrete form of inertia matrix of the object. It can be determined here from a set of x-ray images, at least three images are required. Then, the pose information is obtained fro...

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.575-583
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• 2000

In this paper, a novel estimation alogrithm of mechanical parameters in two-mass system proposed. The inertia of a load and a motor and the stiffness are estimated by using RLS(Recursive Least Square) algorithm and acceleration information of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.427-438
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• 1991

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic system is preented. In the learning control structure, the control input converges globally and asymtotically to the desired input as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of the time-duration of trajectories, it may be achieved with system trajectories with small duration. In addition, the proposd learning control schemes are applicable to time-varying parametric systems as well as time-invariant systems, because the parameter estimation is performed at each fixed time along the iteration. In the parameter estimator, the acceleration information as well as the inversion of estimated inertia matrix are not used at all, which makes the proposed learning control schemes more feasible.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.380-388
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• 2023

This study estimates the metacentric height (GM) of a model ship by varying the transverse weight distribution, considering the effects of the roll period and moment of inertia, and compares it with the GM values measured by the inclining test. In the process, the relationship between the values is analyzed. Three types of ships-a 7-ton fishing vessel, 20-ton fishing vessel, and KRISO Very Large Crude-oil Carrier (KVLCC)-were used for the experiment and comparison. The roll period and moment of inertia were measured using the free roll decay and swing frame tests, and the GM was measured using inclining test. The estimated GM from the roll period and moment of inertia showed the same trend as the GM measured using the inclining test in the change of the weight distribution. However, the GM values measured using the inclining test were lower. Therefore, additional correction factors or parameters other than the roll period and moment of inertia are necessary for estimating GM. In the future, the relationship between the weight center and the estimated GM will be analyzed to derive the correction factors.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.207_208
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• 2009

본 논문에서는 PSS/E(Power system simulator for engineering)를 이용하여 계통 내의 발전기 탈락을 모의하고, 모의 결과로 얻은 주파수의 변동을 이용하여 한국 전체 계통의 시스템 관성상수를 계산하고 특징을 분석하였다. 진동성분이 포함된 시간에 대한 주파수 파형에서 진동성분에 대한 영향을 억제하여 관성상수를 추정하기 위해 주파수 파형을 다항식의 형태로 근사화 하였다. 전체 전력계통은 총 11개의 지역으로 구분하였다. 각 구분된 지역에서의 시스템 관성상수를 추정하였다.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.927-928
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• 2006

본 논문에서는 전동기의 속도제어에 필요한 관성과 마찰계수를 추정하는 알고리즘을 제안한다. 속도관측기에서 발생하는 추정속도와 실제속도로부터 최소자승법을 이용하여 관성과 마찰계수를 동시에 추정한다. 모의실험을 수행하여 추정관성과 추정마찰계수가 제안된 방법에 의하여 각각 실제값에 수렴함을 보인다.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.1043-1050
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• 2011

This paper presents practical results for the estimation of vibration level inside a powertrain based on the rigid body theory and measurement. The vibration level of inside powertrain has been used for the calculation of excitation force of an engine indirectly. However it was difficult to estimate or measure the vibration level inside of a powertrain when a powertrain works on the driving condition of a vehicle. To do this work, the rigid body theory is employed. At the first, the vibration on the surface of a powertrain is measured and its results are secondly used for the estimation the vibration level inside of powertrain together with rigid body theory. Also did research on how to decrease the error rate when the rigid body theory is applied. This method is successfully applied to the estimation of the vibration level on arbitrary point of powertrain on the driving condition at the road.