• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.20-23
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• 1996

This paper deals with the flexible manipulator with rotational and translational degrees of freedom, which has an arm of time-varying length with the prismatic joint. The tracking control problem of the flexible manipulator is considered. First we design the controller of the 2-type robust servo system based on the finite horizon optimal control theory for the trajectory planned as a discontinuous velocity. Next, to reduce the tracking error, we use the method of the dynamic programming and of modifying the reference trajectory in time coordinate. The simulation results show that the dynamic modeling is adequate and that the asymptotic stabilization of the flexible manipulator is preserved in spite of nonlinear terms. The PTP control error has been reduced to zero completely, and the trajectory tracking errors are reduced sufficiently by the proposed control method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.3
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• pp.279-286
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• 2010

In this paper, we provide a robust track-following controller design method for the stable coarse seek control. Due to the inaccurate velocity control during a coarse seek, the shake of fine actuator is generated and thus a gain-up track-following control is required to complete stably the coarse seek. To this end, a loop gain adjustment algorithm is introduced to estimate accurately the shake of fine actuator. A weighting function can be properly selected from a minimum tracking gain-up open-loop gain, calculated from the estimated shake quantity of fine actuator. A robust tracking gain-up controller is designed by considering a robust $H_{\infty}$ control problem using the weighting function. The proposed design method is applied to the coarse seek control system of an optical rewritable drive and is evaluated through the experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.470-477
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• 1990

Singh's multi-level method is extended to the optimal tracking control of a large interconnected dynamical system which has coupled states and coupled inputs. The steady-state tracking error and a convergence condition for the extended multi-level method are derived analytically and the results show that the steady-state tracking error and a convergence rate have to be compromised. Also, a new multi-level method which is advantageous over the Singh's method in steady-state tracking error and computational burden is proposed by introducing nominal inputs into the performance index. The resulting feedback gain matrix and the compensation vector are optimal for all initial conditions so that eventual on-line computation is minimal.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1960-1961
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• 2006

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.6
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• pp.89-99
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• 2008

In this paper proposes a novel tacking algorithm regarding the power loss when operating a tracking system for a rapidly changing insolation to improve the power of PV hacking system. The tracking system of sensor method used in a conventional PV power station is unable to exactly track a sun position when lacking in the intensity of radiation and has the problem is malfunction of tracking system by a rapidly changing climatic. The tracking system of program method spends too much energy on the unnecessary operation of tracking system because that is unable to adapt itself to a outside factor of climatic environment. In case of tracking an azimuth and altitude of the sun in realtime, therefore, the actual PV power is less increasing than the power of tracking system fixed a specific position. To reduce the power loss, this pap proposes a novel control algorithm of the tracking system. Also, this paper is analyzed efficiency of traditional solar tracking method and proposed method, prove validity of proposed algorithm through demonstrable study.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.681-687
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• 2010

In this paper, an implementation of force control for a slave mobile robot in tele-operation environment is presented. A mobile robot is built to have a force control capability with a force sensor and tested for force tracking control performances. Both position and contact force are regulated by a PID based hybrid control method and the impedance force control method. To minimize accumulated errors due to the adaptive impedance force control method, the novel force control method with a weighted function is proposed. Experimental studies of regulating contact forces for different control algorithms are tested and their performances are compared.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.711-719
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• 2010

Heliostat, as a concentrator reflecting the incident solar energy to the receiver located at the tower, is the most important system in the tower-type solar thermal power plant, since it determines the efficiency and performance of solar thermal plower plant. Thus, a good sun tracking ability as well as its good optical property are required. In this paper, we propose a method to compensate the heliostat sun tracking error. We first model the sun tracking error, which could be measured using BCS (Beam Characterization System), by multilayered neural network. Then the extended Kalman filter was employed to train the neural network. Finally the model is used to compensate the sun tracking errors. Simulated result shows that the method proposed in this paper improve the heliostat sun tracking performance dramatically. It also shows that the training of neural network by the extended Kalman filter provides faster convergence property, more accurate estimation and higher measurement noise rejection ability compared with the other training methods like gradient descent method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.2
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• pp.118-128
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• 2012

The goal of this paper is to design the target tracking controller for a quadrotor micro UAV using a vision sensor. First of all, the mathematical model of the quadrotor was estimated through the Prediction Error Method(PEM) using experimental input/output flight data, and then the estimated model was validated via the comparison with new experimental flight data. Next, the target tracking controller was designed using LQR(Linear Quadratic Regulator) method based on the estimated model. The relative distance between an object and the quadrotor was obtained by a vision sensor, and the altitude was obtained by a ultra sonic sensor. Finally, the performance of the designed target tracking controller was evaluated through flight tests.