• 유공압시스템학회논문집
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• 제5권4호
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• pp.26-31
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• 2008

This paper deals with the issue of position tracking control of a clamp-cylinder for injection moulding machine with electric-hydrostatic drives. A fixed displacement pump is utilized in combination with AC motor in order to directly control a clamp-cylinder. A clamp-cylinder may be required to operate under a variety of operating conditions. Therefore, robust control performance is important in position tracking control applications. In order to accommodate mismatches between the real plant and the model used for controller design, discrete-time sliding mode control is developed by combining a velocity feedforward loop. From tracking control experiments, it is shown that significant reduction in position tracking error is achieved through the use of sliding mode control.

• ETRI Journal
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• 제46권3호
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• pp.421-431
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• 2024

In this study, a direct position tracking method for non-circular (NC) signals using distributed passive arrays is proposed. First, we calculate the initial positions of sources using a direct position determination (DPD) approach; next, we transform the tracking into a compensation problem. The offsets of the adjacent time positions are calculated using a first-order Taylor expansion. The fusion calculation of the noise subspace is performed according to the NC characteristics. Because the proposed method uses the signal information from the previous iteration, it can realize automatic data associations. Compared with traditional DPD and two-step localization methods, our novel process has lower computational complexity and provides higher accuracy. Moreover, its performance is better than that of the traditional tracking methods. Numerous simulation results support the superiority of our proposed method.

• Journal of Power Electronics
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• 제7권2호
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• pp.159-173
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• 2007

In this paper, an intelligent sliding-mode position controller (ISMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a sliding-mode position controller (SMC) in the position feed-back loop in addition to an on-line trained fuzzy-neural-network model-following controller (FNNMFC) in the feedforward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with on-line learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the sliding-mode position controller are described with a second order switching surface (PID) which is insensitive to parameter uncertainties and external load disturbances. To realize high dynamic performance in disturbance rejection and tracking characteristics, an on-line trained FNNMFC is proposed. The connective weights and membership functions of the FNNMFC are trained on-line according to the model-following error between the outputs of the reference model and the PMSM servo drive system. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode position controller. The results confirm that the proposed ISMC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.

• 한국정밀공학회지
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• 제25권10호
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.680-684
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• 1996

Welding systems cannot adapt to changes in the joint geometry which may occur due to a variety of reason. Automatic seam tracking technigue is essential to adjust the welding torch position in real time as it moves along the seam. Automatic tracking system must keep the welding speed constant unrelation to the change of the welding path. Therefore, the information from the laser displacement sensor must be converted into the input to operate the X-Y table and to rotate the desired torch position by proposed algorithm. In this research, laser displacement sensor is used as a seam finder in the automatic tracking system. X-Y moving table manipulated by ac servo motor controls the position and velocity of the torch-and-sensor part. DC motor controls the position and velocity of the torch. X-Y table controls the position of sensor and relative position of torch is controlled by dc motor which is mounted at sensor-and-torch part. Sensor is always ahead of torch to preview the weld line. From the experimental results, we could see the possiblity that the laser displacement sensor can be used as a seam finder in welding process and that the seam tracking system controlled by proposed algorithm is well done.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1008-1013
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Velocity is controlled by using an optimal state controller LQR. A position control loop is added to form a PD controller. To minimize a position tracking error, neural network is introduced. The reference compensation technique as a neural network control structure is used, and a position tracking error of an autonomous helicopter is compensated by neural network installed in the remotely located ground station. Considering time delays between an autonomous helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network compensation performs better than that of the LQR itself.

• 전기학회논문지
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• 제60권6호
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• pp.1245-1254
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• 2011

This paper proposes a target tracking algorithm for wheeled mobile robots using in various fields. For the stable tracking, we apply a vision system to a mobile robot which can extract targets through image processing algorithms. Furthermore, this paper presents an algorithm to position the mobile robot at the desired location from the target by estimating its relative position and attitude. We show the problem in the tracking method using the Position-Based Visual Servo(PBVS) control, and propose a tracking method, which can achieve the stable tracking performance by combining the PBVS control with Image-Based Visual Servo(IBVS) control. When the target is located around the outskirt of the camera image, the target can disappear from the field of view. Thus the proposed algorithm combines the control inputs with of the hyperbolic form the switching function to solve this problem. Through both simulations and experiments for the mobile robot we have confirmed that the proposed visual servo control method is able to enhance the stability compared to of the method using only either PBVS or IBVS control method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.5112-5128
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• 2016

Tracking human body is an important problem in computer vision field. Tracking failures caused by occlusion can lead to wrong rectification of the target position. In this paper, a robust human tracking algorithm is proposed to address the problem of occlusion, rotation and improve the tracking accuracy. It is based on Tracking-Learning-Detection framework. The key auxiliary information is used in the framework which motivated by the fact that a tracking target is usually embedded in the context that provides useful information. First, face localization method is utilized to find key face location information. Second, the relative position relationship is established between the auxiliary information and the target location. With the relevant model, the key face information will get the current target position when a target has disappeared. Thus, the target can be stably tracked even when it is partially or fully occluded. Experiments are conducted in various challenging videos. In conjunction with online update, the results demonstrate that the proposed method outperforms the traditional TLD algorithm, and it has a relatively better tracking performance than other state-of-the-art methods.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.752-759
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• 2008

In this paper, we propose a high accurate geo-location system based on a single base station, where its location is obtained by Time-of-Arrival(ToA) and Direction-of-Arrival(DoA) of the radio signal. For estimating accurate ToA and DoA information, a MUltiple SIgnal Classification(MUSIC) is adopted. However, the estimation of ToA and DoA using MUSIC algorithm is a time-consuming process. The position tracking bias is occurred by the time delay caused by the estimation process. In order to mitigate the bias error, we propose the estimation method of the position tracking bias and compensate the location error produced by the time delay using the position tracking bias mitigation. For accurate self-localization of mobile robot, the Unscented Kalman Filter(UKF) with position tracking bias is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.

• Journal of Mechanical Science and Technology
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• 제19권5호
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• pp.1107-1115
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• 2005

In this study, a position and force simultaneous trajectory tracking control algorithm is proposed for a driving apparatus that consists of two pneumatic cylinders connected in series. The controller applied to the driving apparatus is composed of a non-interaction controller to compensate for interaction between cylinders and a disturbance observer aimed to reduce the effect of model discrepancy that cannot be compensated by the non-interaction controller. The effectiveness of the proposed control algorithm is proved by experimental results.