• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.151-156
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• 2014

In this paper, we propose a position estimation method of an entertainment robot in a performance stage. A position information is needed to produce contents of an entertainment robot performance. First, the performance stage is realized by a CD (cadmium sulfide) sensor matrix with a constant distance. Then the proposed position estimation uses ON/OFF information of a CD sensor in a performance stage. We confirmed that the position of the robot is detected with an maximum 4cm in position evaluation experiments. The robot was traveling to the final target position in the walking experiment with 75cm and 120cm path plan. Ultimately, the effectiveness of the proposed estimation is assessed by experimental results of a robot in performance stage. Also, in the proposed system installed by a robot performance contents, there is no necessity to mount a position estimation device on a robot; therefore an advantage of our system is that an entertainment robot commercialized by robot vendor can be utilized in our performance stage directly.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.2
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• pp.139-146
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• 2018

This work puts forward a theoretical analysis on position estimation performance of interior permanent magnet synchronous motor (IPMSM) according to the injection frequency in carrier-based sensorless operation. The effects of spatial harmonics on inductance and voltage distortion due to the nonideal characteristics of IPMSM and inverter are examined as factors influencing the position estimation performance. Furthermore, the position estimation performance is analyzed by calculating the current at the switching instant in several operating conditions. In summary, the half switching frequency injection is more robust to the nonideal characteristics of IPMSM, especially with light load condition. The validity of the analysis is verified by the simulation and experimental results.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.104-108
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• 2003

This paper explained algorithm for a initial pole position estimation of a permanent magnet linear synchronous motor(PMLSM). Generally this motor is considered initial pole position with a position sensor such as incremental encoder for the precise initial pole position estimation and high performance. But this is based on the principle that the initial pole position is accomplished by the PI controller using the maximum values of a position error generated by the new proposed two reference frames and also by using a rated force for input. the proposed algorithm does not utilize the general methods such as impedance ratio, EMF and using the magnetic saturation. In other words, this can be applied without respect to variety of the motor structure because of insensitivity to the motor parameters. In conclusion, simulation results are presented to confirm performance of initial pole position estimation method.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.200-202
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• 2005

In this paper, improved rotor position estimation for position sensorless control system of the SRM (Switched Reluctance Motor) is presented. For more accurate rotor position estimation, the PLL (Phase Locked Loop) based position interpolation is adapted. In the current-flux-rotor position lookup table based rotor position estimation, the inherent current and flux-linkage ripple can cause the position estimation error. Instead of the conventional low-pass filter, the PLL based position interpolation technique is used for the better dynamic performance. The developed rotor position estimation scheme is realized using TMS320F2812 digital signal processor and prototype 1-hp SRM.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.123-128
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• 2021

This paper present box feature estimation from LiDAR point cluster using maximum likelihood Method. Previous LiDAR tracking method for autonomous driving shows high accuracy about velocity and heading of point cluster. However, Assuming the average position of a point cluster as the vehicle position has a lower accuracy than ground truth. Therefore, the box feature estimation algorithm to improve position accuracy of autonomous driving perception consists of two procedures. Firstly, proposed algorithm calculates vehicle candidate position based on relative position of point cluster. Secondly, to reflect the features of the point cluster in estimation, the likelihood of the particle scattered around the candidate position is used. The proposed estimation method has been implemented in robot operating system (ROS) environment, and investigated via simulation and actual vehicle test. The test result show that proposed cluster position estimation enhances perception and path planning performance in autonomous driving.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.117-123
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• 2017

In this paper, we propose a performance index that can compare the position estimation performance according to the time slot allocation order, which is superior in the position estimation performance in the operation of the Link-16 based relative navigation system. In order to verify the validity of the performance index, a software-based Link-16 relative navigation system performance analysis platform composed of a signal generator, a signal reception and navigation algorithm execution unit, and a performance analysis unit was designed. Using the designed software platform, we analyzed the relationship between proposed performance index and position estimation performance according to time slot allocation order in the same position reference (PR) arrangement. The performance index of the proposed time slot allocation is expected to be utilized not only for the Link-16 system, but also for the Time Division Multiple Access (TDMA)-based navigation system.

• Journal of Magnetics
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• v.19 no.1
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• pp.90-100
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• 2014

Position estimation that uses only active phase voltage and current is presented, to perform high accuracy position sensorless control of a SRM drive. By extracting the amplitude of the first switching harmonic terms of phase voltage and current for a PWM period through Fast Fourier Transform (FFT), the flux-linkage and position are estimated without external hardware circuitry, such as a modulator and demodulator, which result in increased cost, as well as large position estimation error, produced when the motional back EMF is ignored near zero speed. A two-phase SRM drive system, consisting of an asymmetrical converter and a conventional closed-loop PI current controller, is utilized to validate the performance of the proposed position estimation scheme in comprehensive operating conditions. It is shown that the estimated values very closely track the actual values, in dynamic simulations and experiments.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.2
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• pp.184-189
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• 2013

This paper proposes a method for improving the performance of a position sensorless control system for a slotless surface permanent magnet synchronous motor (SPMSM) in a very low-speed region. In position sensorless control based on a motor model, accurate motor parameters are required because parameter errors would affect position estimation accuracy. Therefore, online parameter identification is applied in the proposed system. The error between the reference voltage and the voltage applied to the motor is also affect position estimation accuracy and stability, thus it is compensated to ensure accuracy and stability of the sensorless control system. In this study, two voltage error compensation methods are used, and the effects of the compensation methods are discussed. The performance of the proposed sensorless control method is evaluated by experimental results.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.202-207
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• 2016

Estimation of vertical position is critical in applications of sports science and fall detection and also controls of unmanned aerial vehicles and motor boats. Due to low accuracy of GPS(global positioning system) in the vertical direction, the integration of IMU(inertial measurement unit) with the GPS is not suitable for the vertical position estimation. This paper investigates an IMU-barometer integration for estimation of vertical position (as well as vertical velocity). In particular, a new two-step Kalman/complementary filter is proposed for accurate and efficient estimation using 6-axis IMU and barometer signals. The two-step filter is composed of (i) a Kalman filter that estimates vertical acceleration via tilt orientation of the sensor using the IMU signals and (ii) a complementary filter that estimates vertical position using the barometer signal and the vertical acceleration from the first step. The estimation performance was evaluated against a reference optical motion capture system. In the experimental results, the averaged estimation error of the proposed method was 19.7 cm while that of the raw barometer signal was 43.4 cm.