• Journal of Power Electronics
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• v.14 no.6
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• pp.1243-1253
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• 2014

The phase inductance of a switch reluctance motor (SRM) is significantly nonlinear. With different saturation conditions, the phase inductance shape is clearly changed. This study focuses on the relationship between coefficient and current in an inductance model with ignored harmonics above the order of 3. A position estimation method based on the variable coefficient inductance model is proposed in this paper. A four-quadrant sensorless control system of the SRM drive is constructed based on the relationship between variable coefficient inductance and rotor position. The proposed algorithms are implemented in an experimental SRM test setup. Experimental results show that the proposed method estimates position accurately in operating two/four-quadrants. The entire system also has good static and dynamic performance.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.34-36
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• 2002

This paper addresses an elevator position control scheme in unified control system. Conventional systems have employed independent micro-processors for speed, car, and group control respectively and the car controller generates a velocity command by combining the time-based and distance-based velocity pattern. In this scheme, it is inevitable that an elevator creeps in the vicinity of target floor, or stops abruptly. The proposed control system employs only one high-performance micro-processor, which can execute the car and group control as well as the speed control. It simply generates the desired position trajectory based on time and on-line corrects a velocity pattern to make the position error be zero. Experimental results show the feasibility of the proposed control scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.855-861
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• 2007

In real system application, the IMM-based position tracking algorithm requires robust performance, less computing resources and easy design procedure with respect to the uncertain target maneuvering, To solve these problems, an adaptive fuzzy interacting multiple model (AFIMM) algorithm, which is based on the well-defined basis sub-models and well-adjusted mode transition probabilities (MTPs), is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application of the IMM-based position tracking algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.3
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• pp.270-275
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• 2017

This paper proposes a double-phase-locked-loop (PLL) to improve the performance of position estimation in hall sensor-based permanent magnet synchronous motor control. In hall sensor-based control, a PLL is normally used to estimate the rotor position. The proposed Double-PLL consists of two PLLs, including a reset type integrator. The motor control is more accurate and has better performance than conventional PLL, such as a small estimated position ripple. The validity of the proposed algorithm is verified by simulations and experiments.

• Journal of Sensor Science and Technology
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• v.31 no.3
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• pp.139-144
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• 2022

Advanced tactile sensors are receiving significant attention in various industries such as extended reality, electronic skin, organic user interfaces, and robotics. The capabilities of advanced tactile sensors require a variety of functions, including position sensing, pressure sensing, and material recognition. Moreover, they should comsume less power and be bio-friendly with human contact. Recently, a tactile sensor based on the triboelectrification effect was developed. Triboelectric tactile sensors have the advantages of wide material availability, simple structure, and low manufacturing cost. Because they generate electricity by contact, they have low power consumption compared to conventional tactile sensors such as capacitive and piezoresistive. Furthermore, they have the ability to recognize the contact material as well as execute position and pressure sensing functions using the triboelectrification effect. The aim of this study is to introduce the progress of research on triboelectrification-based tactile sensors with various functions such as position sensing, pressure sensing and contact material recognition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.8-15
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• 2019

The PM synchronous motor drives with vector control have been applied to wide fields of industry applications due to its high efficiency. The rotor position information for vector control of a PM synchronous motor is detected from the rotor position sensors or rotor position estimators. The sensorless control based on the mathematical model of PM synchronous motor is generally used and it can be classified into back EMF -based sensorless control and magnet flux-based sensorless control. The rotor position estimating performance of the back EMF-based sensorless control is deteriorated at low speeds since the magnitude of back EMF is proportional to the motor speed. The magnitude of the magnet flux for estimating rotor position in the flux-based sensorless control is independent on the motor speed so that the estimating performance is excellent for wide speed ranges. However, the estimation performance of the model-based sensorless control may be influenced by the motor parameter variation since the rotor position estimator uses the mathematical model of the PM synchronous motor. In this paper, the rotor position estimation performance for the back EMF based- and flux-based sensorless controls is analyzed theoretically and is compared through the simulation and experiment when the motor parameters including stator resistance and inductance are varied.

• Journal of Navigation and Port Research
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• v.29 no.7
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• pp.611-614
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• 2005

This paper is to develop the position error equation of in the free-gyro positioning system by using two free gyros. First, the determination of a position is analyzed on the ellipsoid of the Earth and the type of the errors is defined Finally the position error equation is introduced and developed, based on the definition of the type of errors which may be involved in the FPS.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• Journal of Power Electronics
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• v.13 no.2
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• pp.264-274
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• 2013

A new sensorless position estimation method for switched reluctance motor (SRM) drives is presented in this paper. This method uses the change of the slope of the phase inductance to detect the aligned position. Since the aligned positions for successive electrical cycle of each phase are apart by a fixed mechanical angle $45^{\circ}$ in the case of 12/8 SRM, the speed of the machine can be calculated to estimate the rotor position. Since no prior knowledge of motor parameters is required, the method is easy for implementation without adding any additional hardware or memory. In order to verify the validity of this technique, effects such as changes in the advanced angle and phase lacking faults are examined. In addition, an inductance threshold based sensorless starting scheme is also proposed. Experimental results demonstrate the validity of the proposed method.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.70-76
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• 2020

Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.