• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.389-392
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• 1996

We propose a method to improve repeatability positioning precision of a linear pulse motor. By using this method the systematic error which may make the precision worse can be suppressed easily. And also we show that Power OP-Amp drive system enables the accidental error to be suppressed in comparison with PWM control drive system using IGBT inverter. As a result of the suppression of systematic and accidental error, improved performance of a linear pulse motor with repetitive positioning control is shown by experimental results.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.62-68
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• 2002

To satisfy the requirement of the one axis linear positioning system, which is following control of the desired trajectory without following error and is the high positioning accuracy, feed-forward loop having cogging force model is proposed. In the one axis linear positioning system with linear PM motor, cogging force acting as disturbance is modeled analytically. Analytic model of cogging force is verified by result measured from positioning system constructed with linear PM motor. Measured result is very similar with proposed analytic model. Cogging force model is used as feet forward loop in control scheme of linear positioning system. Cogging force feed-forward'loop is obtained from analytic model of cogging farce. Trajectory following error is reduced from 300nm to 100nm by applying the proposed cogging farce feed-forward loop. By using analytic model of cogging force, the control scheme is simplified. Also this analytic model is applicable to calculation of characteristic value of positioning system in design process.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.684-690
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• 2015

This paper presents a modified residual-based EKF (Extended Kalman Filter) for performance improvement of indoor positioning using WiFi RSSI (Received Signal Strength Indicator) measurement. Radio signal strength in indoor environments may have irregular attenuation characteristics due to obstacles such as walls, furniture, etc. Therefore, the performance of the RSSI-based positioning with the conventional trilateration method or Kalman filter is insufficient to provide location-based accurate information services. In order to enhance the performance of indoor positioning, in this paper, error analysis of the distance calculated by using the WiFi RSSI measurement is performed based on the radio propagation model. Then, an IARM (Irregularly Attenuated RSSI Measurement) error is defined. Also, it shows that the IARM error is included in the residual of the positioning filter. The IARM error is always positive. So, it is presented that the IARM error can be estimated by taking the absolute value of the residual. Consequently, accurate positioning can be achieved based on the IEM (IARM Error Mitigated) EKF with the residual modified by using the estimated IARM error. The performance of the presented IEM EKF is verified experimentally.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.774-781
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• 2014

This paper presents a fingerprint database construction method for WLAN RSSI (Received Signal Strength Indicator)-based indoor positioning. When RSSI is used for indoor positioning, the fingerprint method can achieve more accurate positioning than trilateration and centroid methods. However, a FD (Fingerprint Database) must be constructed before positioning. This step is a very laborious process. To reduce the drawbacks of the fingerprint method, a radio propagation model-based FD construction method is presented. In this method, an FD can be constructed by a simulator. Experimental results show that the constructed FD-based positioning has a 3.17m (CEP) error. In this paper, a spatial correlation method is presented to estimate the NLOS(Non-Line of Sight) error included in the FD constructed by a simulator. As a result, the NLOS error of the FD is reduced and the performance of the error compensated FD-based positioning is improved. The experimental results show that the enhanced FD-based positioning has a 2.58m (CEP) error that is a reasonable performance for indoor LBS (Location Based Service).

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.962-967
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• 2006

Indoor positioning is highlighted recently, and various kinds of indoor positioning systems are under developments. Since positioning systems have their own characteristics, proper positioning scheme should be chosen according to the required specifications. Positioning methods are classified into time-based and angle-based one. This paper presents the error analysis of time-based and angle-based location methods. Because measurements of these methods are nonlinear, linearizations are needed in both cases to estimate the user position. In the linearization, Gauss-Newton method is used in both cases. To analyze the position error, we investigate the error ellipse parameters that include eccentricity, rotation angle, and the size of ellipse. Simulation results show that the major axes of TOA and AOA method lie in different quadrants at most region of workspace, especially where the geometry is poor. When the TOA/AOA hybrid is employed, it is found that the error ellipse is reduced to the intersection of ellipses of TOA and AOA.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.266-272
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• 1994

An essential ingredient in precision machining is a positioning system that responds quickly and precisely to very small input signal. In this paper, two different positioning systems were presented fot the precision positioning control. The one is a friction drive system, the other is a ballscrew system. The friction drive system was composed of an air sliding guide and a friction drive. The ballscrew system was made of a ballscrew and a linear guide. Nonlinear behaviors of the given systems tend to make the system inaccurate. The paper looked at the phenomena that has caused the positioning error. These apparently nonlinear phenomena can be attributed mainly to the presence of the nonlinear friction and slip effect plus the dynamic change from the microdynamic to the macrodynamic and form the macrodynamic to the microdynamic. For the control of the positioning system, the control algorithm based on a neural network is suggested. The FEL(Feedback Error Learning) controller can learn the inverse dynamics of a nonlinear system by using the neural network controller, and stabilize the system by a linear controller. In the experiment, PTP control is implemented withen the maximum error of 0.05 .mu.m ~0.1 .mu. m when i .mu.m step reference input is applied and that of maximum 1 .mu. m when 100 .mu.m step reference input is given. Sinusoidal inputs with the amplitude of 1 .mu.m and 100 .mu. m are used for the tracking control of the positioning system. Experimental results of the proposed algorithm are shown to be superior to those of conventional PD controls.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.550-557
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• 2001

There are several applications and error analysis methods using GPS(Global Positioning System) In most analysis positioning and timing errors are represented as the multiplication of DOP(Dilution Of Precision) and measurement errors, which are affected by the receiver and measurement type. Therefore, lots of DOPs are defined and used to analyze and predict the performance of positioning and timing systems. In this paper, the relationships between these DOPs are investigated in detail, The relationships between GDOP(Geometric DOP), PDOP(Position DOP) and TDOP(Time DOP) in the absolute positioning are de-rived. Using these relationships, the affect of clock bias is analyzed. The relationships between RGDOP(Relative DOP) and PDOP are also derived in relative positioning where the single difference and double dif-ference techniques are used. From the results, it is expected that using the common clock will give better performance when the single difference technique is used while the effects of clock is eliminate when the double difference technique is used. Finally, the error analyses of dual frequency receivers show that the narrow lane measurements give more accurate results than wide line of or L1. L2 independent measurements.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.10
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• pp.997-1005
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• 2008

Linear motor stage is a useful device in precision engineering field because of its simple power transmission mechanism and accurate positioning. Even though linear motor stage shows fine positioning accuracy along travel axis, geometric dependent errors which relay on machining and assembling accuracy should be addressed to increase total positioning performances. In this paper, we suggests a cost effective yaw error compensation servo-system which is mounted on platform of the stage and nullify travel position dependent yaw error. This paper also provides a method of designing a sliding mode control which is robust to existing friction disturbance and model uncertainties. The reachability condition of slinding mode control for the yaw error compensating servo-system has been established. From some experimental results by using an experimental set-up, the sliding mode control showed its effective in disturbance rejection and its performance was superior to conventional linear controls.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.898-902
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• 2015

Alternative radio-navigation technologies aim at providing continuous navigation solution even if one cannot use GNSS (Global Navigation Satellite System). In shadowing region such as indoor environment, GNSS signal is no longer available and the alternative navigation system should be used together with GNSS to provide seamless positioning. For soldiers in battlefield where GNSS signal is jammed or in street battle, the alternative navigation system should work without positioning infrastructure. Moreover, the radio-navigation system should have scalability as well as high accuracy performance. This paper presents a TWR (Two-Way-Ranging)-based cooperative positioning system (CPS) that does not require location infrastructure. It is assumed that some members of CPS can obtain GNSS-based position and they are called mobile anchors. Other members unable to receive GNSS signal compute their position using TWR measurements with mobile anchors and neighboring members. Error propagation in CPS is analytically studied in this paper. Error budget for TWR measurements is modeled first. Next, location error propagation in CPS is derived in terms of range errors. To represent the location error propagation in the CPS, Location Error Propagation Indicator (LEPI) is proposed in this paper. Simulation results show that location error of tags in CPS is mainly influenced by the number of hops from anchors to the tag to be positioned as well as the network geometry of CPS.

• Journal of Power System Engineering
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• v.17 no.5
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• pp.100-111
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• 2013

Indoor real-time positioning for multiple targets is required to realize human-robot symbiosis. This study firstly presents positioning accuracy on an autonomous mobile robot controlled by 3-D coordinates that is obtained by a real-time indoor positioning system with spread spectrum (SS) ultrasonic signals communicated by code-division multiple access. Although many positioning systems have been investigated, the positioning system with the SS ultrasonic signals can measure identified multiple 3-D positions in every 70 ms with noise tolerance and error within 100 mm. This system is also robust to occlusion and environmental changes. However, thus far, the positioning errors in an autonomous mobile robot, controlled by these systems using the SS ultrasonic signals, have not been evaluated as an experimental study. Therefore, a positioning experiment for trajectory control is conducted using an autonomous mobile robot and our positioning system. The effectiveness of this positioning method for robot self-localization is shown, from this experiment, because the average control error between the target position and the robot's position at 29 mm is obtained.