• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.930-935
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

• Transactions of The Korea Fluid Power Systems Society
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• v.5 no.4
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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.

• Journal of Power Electronics
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• v.10 no.4
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• pp.405-411
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• 2010

This paper proposes a novel tracking algorithm considering radiation to improve the power of a photovoltaic (PV) tracking system. The sensor method used in a conventional PV plant is unable to track the sun's exact position when the intensity of solar radiation is low. It also has the problem of malfunctions in the tracking system due to rapid changes in the climate. The program method generates power loss due to unnecessary operation of the tracking system because it is not adapted to various weather conditions. This tracking system does not increase the power above that of a power of tracking system fixed at a specific position due to these problems. To reduce the power loss, this paper proposes a novel control algorithm for a tracking system and proves the validity of the proposed control algorithm through a comparison with the conventional PV tracking method.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.164-168
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• 1988

This paper utilizes an optimal control law for the accurate tracking servo system design. The devivation of a simple control law implementing microprocessor is made to minimize position and speed error of the controller. The 16 bit microprocessor receives command angular position and calculate the control algorithm for accurate tracking and provides control system gain scheduling to achieve very short settling time. Simulation results and some experimental results of the position controlled tracking using 4.5Kw DC servo motor are shown.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.932-935
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• 1996

This paper proposes position estimation and path-tracking of a wheeled-mobile robot(WMR). Odometry and two distance measuring sensors are used to measure distance between guide wall and body and to locate its own position. And extended Kalman filter is introduced to fusion sensors and reduce noise. State feedback controller using the estimated position and path-tracking miles guidance control system. The computer simulation shows that proposed algorithm is well coincide with theoretical approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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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.

• Journal of Power Electronics
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• v.9 no.1
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• pp.74-84
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• 2009

The design and implementation of a high performance PID (Proportional Integral & Differential) style controller with zero-phase error tracking property is considered in this article. Unlike a ball screw driven system, the controller in a direct drive system should provide a high level of tracking performance while avoiding the problems due to the absence of the gear system. The stiff mechanical element in a direct drive system allows high precise positioning capability, but relatively high tracking ability with minimal position error is required. In this work, a feasible position controller named 'Unified PID controller' is presented. It will be shown that the function of the closed position loop can be designed into unity gain system in continuous time domain to provide minimal position error. The focus of this work is in two areas. First, easy gain tunable PID position controller without speed control loop is designed in order to construct feasible high performance drive system. Second, a simple but powerful zero phase error tracking strategy using the pre-designed function of the main control loop is presented for minimal tracking error in all operating conditions. Experimental results with a s-curve based position pattern commonly used in industrial field demonstrate the feasibility and effective performance of the approach.

• Journal of Power Electronics
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• v.7 no.2
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.296-304
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• 2002

A position tracking control schemes on the precise mechanical system in presence of nonlinear dynamic friction is proposed. A nonlinear dynamic friction is regarded as the bristle friction model to compensate effects of friction. The conventional sliding mode controller often has been used as a non-model-based friction controller, but it has a poor tracking performance in high-precision position tracking application since it completely cannot compensate the friction effect below a certain precision level. Thus to improve the precise position tracking performance, we propose the sliding mode control method combined with the friction-model-based observer having tunable structure of the transient response. Then this control scheme has a good transient response as well as the high precise tracking performance compared with the conventional sliding mode control without observer and the control system with similar type of observer. The experiments on the bali-screw drive table with the nonlinear dynamic friction show the feasibility of the proposed control scheme.