• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.350-355
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• 1997

The problem of mathematical model for an unknown system by measureing its input-output data pairs is generally referred to as state estimates. The state estimation problem is often of importance in its own right since we may want to know the value of the states. For instance, in navigation, we may take noisy positional fixes using satelite or radar navigation, and the estimator can use these measurements to provide accurate estimates of current position, hedaing, and velocity. And the state estimates can also be used for control purposes. Then it is very important to know the state of plant. In this paper, the theory of the minimization of a loss function was used to design the fuzzy system. Here, the used teory is Least Square Esimation method. This parametrization has the Linear in the parameters charcteristic that allows standard parameter estimation technique to be used to estimate the parameters of the fuzzy system. The combination of the fuzzy system and the estimation m thod then performs as a nonlinear estimator. If several fuzzy label are defined for the input variables at the antecedent part, the fuzzy system then behaves as a collection of nonlinear estimators where different regions of rules have different parameters. In simulation results, the fuzzy model controlled a difference in the structure between the actual plant and the fuzzy estimator. It is also proved that the fuzzy system is equivalent to its transformed system. therefore we was able to get the state space equation of system with the estimated paramater.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.528-530
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• 1999

This paper addresses the analysis and design of fuzzy control systems for a class of complex single input single output nonlinear systems. Firstly, the nonlinear system is represented by well-known Takagai-Sugeno (TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller usually is composed of two processes. One is to determine static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative of the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. One simulation example is given to show the effectiveness and feasibility of the proposed fuzzy controller design method.

• 제어로봇시스템학회논문지
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• 제11권7호
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• pp.609-614
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• 2005

Parallel manipulators have been used for a variety of applications, including the motion simulators and mechanism for precise machining. Since the ball screws used for linear motion of legs of the Stewart-Gough type parallel manipulator provide wider contact areas than revolute joints, parallel manipulators are usually more affected by frictional forces than serial manipulators. In this research, the method for detecting the frictional forces arising in the parallel manipulator using the gravitational force is proposed. First, the reference trajectories are computed from the dynamic model of the parallel manipulator assuming that it is subject to only the gravitational force without friction. When the parallel manipulator is controlled so that the platform follows the computed reference trajectory, this control force for each leg is equal to the friction force arising in each leg. It is shown that control performance can be improved when the friction compensation based on this information is added to the controller for position control of the moving plate of a parallel manipulator.

• 제어로봇시스템학회논문지
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• 제21권9호
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• pp.818-826
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• 2015

This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

• Journal of Mechanical Science and Technology
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• 제15권7호
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• pp.847-858
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• 2001

This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

• 대한조선학회논문집
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• 제45권5호
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• pp.469-476
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• 2008

In this paper, it is shown that an input-output (I/O) feedback linearized controller can be designed rationally by utilizing the time-scale properties of heave and pitch for an underwater vehicle. It is assumed that the dynamics of the vehicle is restricted to the vertical plane. An output-feedback control is designed, which stabilizes steady cruising paths. It is shown that the vehicle dynamics with acceleration as output becomes minimum phase. The dynamics can be transformed into a reduced system through a kind of partial linearization and singular perturbation technique. The reduced system is not only minimum phase but also exactly I/O linearizable via feedback. The I/O dynamic characteristics of the heave and pitch modes can be made linear and decoupled. Furthermore it becomes independent of cruising condition such as vehicle velocity. This study may help for designing autopilot systems for underwater vehicles.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.623-625
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• 2000

For the finite element analysis of highly saturated rotating machines involving rotation of a rotor such as dynamic analysis. cogging torque analysis and etc, so much time is needed because a new system matrix equation should be solved for each iteration and time step. It is proved in this paper that. in linear systems. the computational time can be greatly reduced by using the domain decomposition method (DDM). In nonlinear systems. however. this advantage vanishes because the stiffness matrix changes at each iteration especially when using the Newton-Raphson (NR) method. The transmission line modeling (TLM) method resolves this problem because in TLM method the stiffness matrix does not change throughout the entire analysis. In this paper, a new technique for FEA of rotating machines including rotation of rotor and non-linearity is proposed. This method is applied to a test problem. and compared with the conventional method.

• ETRI Journal
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• 제42권5호
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.1015-1023
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• 2001

error behaviour can be considered as a linear combination of low amplitude random noise and abrupt jumps. The reason of jump appearance can be explained by the semi-shading effects(buildings, trees), jamming, high dynamic of vehicle and so on. This study describes the stand-alone GPS error jump smoothing algorithm which is developed based on the scalar adaptive filter. The algorithm consists of the coarse jump smoothing and the fine jump smoothing. On the coarse smoothing step, GPS velocities or position differences are used as the measurement for the scalar adaptive filter. The purpose of adaptive filter is to smooth the jump errors. The coarse positions are detennined by the integration of smoothed velocities. On the fine smoothing step, the differences between GPS positions and the coarse positions are smoothed by another scalar adaptive filter. The reason of fine smoothing is based on the facts that smoothing accuracy depends on the variance ofusefuJ signa\. The coarse smoothing which deal with the difference of positions provides the rough error removing. So the coarse smoothed velocities can have much more low amplitude than the raw ones. The fine smoothing procedure provides high quality of filtering process. Simulation results show the efficiency of proposed scheme.

• 제어로봇시스템학회논문지
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• 제15권5호
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• pp.496-504
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• 2009

This paper presents a recognition performance of VOR (Vestibular-Ocular Reflex) based vision tracking system for mobile robot. The VOR is a reflex eye movement which, during head movements, produces an eye movement in the direction opposite to the head movement, thus maintaining the image of interested objects placed on the center of retina. We applied this physiological concept to the vision tracking system for high recognition performance in mobile environments. The proposed method was implemented in a vision tracking system consisting of a motion sensor module and an actuation module with vision sensor. We tested the developed system on an x/y stage and a rate table for linear motion and angular motion, respectively. The experimental results show that the recognition rates of the VOR-based method are three times more than non-VOR conventional vision system, which is mainly due to the fact that VOR-based vision tracking system has the line of sight of vision system to be fixed to the object, eventually reducing the blurring effect of images under the dynamic environment. It suggests that the VOR concept proposed in this paper can be applied efficiently to the vision tracking system for mobile robot.