• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.45-53
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• 2004

In this paper, an INS compensation algorithm for auto sailing system is proposed, where low cost IMU (Inertial Measurement Unit) is used for measuring the accelerometer data. First, we denote the basic INS algorithm with IMU and show that how to compensate the error of position by using low cost IMU. Second, in considering the ship's characteristic and ocean environments, we consider with a factor as a periodic external disturbance which effects to the exact position. To develop the compensation algorithm, we use a repetitive method to reduce the external environment changes. Lastly, we verify the proposed algorithm by using experiments results.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.534-540
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• 1993

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algrithms need a special perfect position sensor or a priori information about error sources, while ours does not. To our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterative learning algorithm does not have the drawbacks of the existing iterative learning control theories. To be more specific, our algorithm learns a uncertain function inself rather than its special time-trajectory and does not request the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1190-1199
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• 2016

This study proposes a classification and compensation algorithm of two non-ideal output signals of a resolver to reduce position errors. Practically, a resolver generates position errors because of amplitude imbalance and quadrature imperfection between the two output signals of the resolver. In this study, a digital signal processor system based on a resolver-to-digital converter is used to reconstruct the two output signals of the resolver. The two output signals, "sin" and "cos," can be represented by a unit circle on the xy-plot. The classification and compensation of the errors can be obtained by using the radius and area of the circle made by the resolver signals. The method computes the integration of the areas made by the two resolver output signals to classify and compensate the error. This system cannot be applied during transient response given that the area integration during the transient state causes an error in the proposed method. The proposed method does not need any additional hardware. The experimental results verify the effectiveness of the proposed algorithm.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2708-2715
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• 2021

The Multi-Purpose Overload Robot (CMOR) is a key subsystem of China Fusion Engineering Test Reactor (CFETR) remote handling system. Due to the long cantilever and large loads of the CMOR, it has a large rigid-flexible coupling deformation that results in a poor position accuracy of the end-effector. In this study, based on the Levenberg-Marquardt algorithm, the spatial grid, and the linearized variable load principle, a variable parameter compensation model was designed to identify the parameters of the CMOR's kinematics models under different loads and at different poses so as to improve the trajectory tracking accuracy. Finally, through Adams-MATLAB/Simulink, the trajectory tracking accuracy of the CMOR's rigid-flexible coupling model was analyzed, and the end position error exceeded 0.1 m. After the variable parameter compensation model, the average position error of the end-effector became less than 0.02 m, which provides a reference for CMOR error compensation.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1310-1319
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• 2013

Resolvers are transducers that are used to sense the angular position of rotational machines. The analog resolver is necessary to use resolver to digital converter. Among the RDC software method, angle tracking observer (ATO) is the most popular method. In an actual resolver-based position sensing system, amplitude imbalance dominantly distorts the estimate position information of ATO. Minority papers have reported position error compensation of resolver's output signal with amplitude imbalance. This paper proposes new ATO algorithm in order to compensate position errors caused by the amplitude imbalance. There is no need premeasured off line data. This is easy, simple, cost-effective, and able to work on line compensation. To verify feasibility of the proposed algorithm, simulation and experiments are carried out.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.57-66
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• 1994

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algorithms need a special perfect position sensor or a priori information about error sources, while ours does not. to our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterativelearning algorithm does not have the drawbacks of the existing interativelearning control theories. To be more specivic, our algorithm learns an uncertain function itself rather than its special time-trajectory and does not reuquest the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.497-502
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• 1997

In this study an automatic rolling-coil labeling system using robot vision system and peripheral mechanism is proposed and implemented, which instead of the manual labor to attach labels Rolling-coils in a steel mill. The binary image process for the image processing is performed with the threshold, and the contour line is converted to the binary gradient which detects the discontinuous variation of brightness of rolling-coils. The moments invariant algorithm proposed by Hu is used to make it easy to recognize even when the position of the center are different from the trained data. The position error compensation algorithm of six degrees of freedom industrial robot manipulator is also developed and the data of the position of the center rolling-coils, which is obtained by floor mount camera, are transferred by asynchronous communication method. Therefore, even if the position of center is changed, robot moves to the position of center and performs the labeling work successfully. Therefore, this system can be improved the safety and efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1144-1148
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• 1996

This paper presents WMR modelling and path tracking algorithm using Inertial Navigation System. The error models of gyroscope and accelerometers in INS are derived by Gauss-Newton method which is nonlinear regression model. Then, to test availability of error model, we pursue the fitness diagnosis about probability characteristic for real data and estimated data. Performance of inertial sensor with error model and Kalman filter is pursued by comparing with one without them. The computer simulation shows that position error remarkably decrease when error compensation is applied.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2701-2706
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• 2003

This paper describes weld seam tracking and error compensation methods of automatic plasma arc welding system designed for the corrugation panel that consists of a linear section and a curved section with various curvatures. Realizing automatic welding system, we are faced with two problems. One is a precise seam tracking and the other is an arc length control. Due to the complexity of the panel shape, it is difficult to find a seam and operate a torch manually in the welding process. So, laser vision sensor for seam tracking is equipped for sensing the seam position and controlling the height of a torch automatically. To attain more precise measurement of an arc length, we measure the 3D shape of the panel and analyze error factors according to the various panel states and caused errors are predicted through the welding process. Using that result, compensation algorithm is added to that of arc length control and real time error compensation is achieved. The result shows that these two methods work effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.