• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.722-725
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• 1996

This paper presents a new control strategy for the position and force control of a flexible manipulator. The governing equation of motion of a two-link flexible manipulator which features a piezoceramic actuator is derived via Hamilton's principle. The control torque of the motor to command desired position and force is determined by a sliding mode controller. This controller is formulated to take account of parameter uncertainties and external disturbances. During the commanded motion, undesirable oscillation is actively suppressed by applying a feedback control voltage to the piezoceramic actuator. Consequently, an accurate compliant motion control of the flexible manipulator is achieved. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control methodology.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.257-262
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• 1996

When we are estimate the smoothing parameter in spline regression model, we deal the diagnostic of influence observations as posteriori analysis. When we use Generalized Maximum Likelihood Function as the estimation method of smoothing parameter, we propose the diagnostic measure for influencial observations in the obtained estimate, and we introduce the finding method of the proper smoothing parameter estimate.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.413-418
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• 2012

This paper presents a multi-robot path planner for environment exploration and monitoring. Robotics systems are being widely used as data measurement tools, especially in dangerous environment. For large scale environment monitoring, multiple robots are required in order to save time. The path planner should not only consider the collision avoidance but efficient coordination of robots for optimal measurements. Nonlinear spring force based planning algorithm is integrated with the spatial gradient following path planner. Perturbation/Correlation based estimation of spatial gradient is applied. An algorithm of tuning the stiffness for robot coordination is presented. The performance of the proposed algorithm is discussed with simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.340-346
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• 1996

In this paper, we propose a ne weighted backward covariance matrix method to enhance the resolution for direction-of-arrival(DOA) estimation. The proposed method (MEVM:modified eigenvector method) is an enhanced covariance matrix method which is an extended form of the conventional covariance matrix. We analyze the effect of using the weighted forward-baskward covariance matrix on the performance of the eigenvector method(EVM). By comparing the perturbation angle of the noise-subspace, we show that the spectral estimate obtained using the proposed method is less distorted than the spectral estimate obtained using the conventional EVM. The simulation results show that the new method is more accurate and has better resolution than the conventional EVM under the same noise conditions.

• Proceedings of the Acoustical Society of Korea Conference
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• 1996.06a
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• pp.45-50
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• 1996

천해에서 얻은 잔향음신호를 역추정 알고리즘으로 분석하여 자료수집 당시의 환경 변수인 해상풍의 세기와 해저면의 상태를 추정하는 방법에 대하여 기술하였다. 소오나 시스템과 잔향음신호 수집 당시의 환경 자료를 알고 있다면 음원에서 방사된 음파가 해수면에 처음 도달하는 시간과 수평입사각을 multipath eigenray model에 의해서 계산할 수 있고 이 정보를 이용하여 수신된 잔향음 신호를 분석하여 해수면에 의한 산란잔향음 준위와 시간을 계산할 수 있다. 해수면 후방산란강도는 수평입사각, 음원의 주파수, 해상풍의 세기 등에 의해 특징지어지며 계산된 잔향음 준위로부터 소오나 방정식을 이용하여 후방산란강도를 알아낼 수 있다. 이 후방산란강도를 입력자료로 하여 Method of Small Perturbation이론과 Chapman과 Harris가 유도한 실험식을 사용하여 입력된 값과 일치할 때까지 후방산란강도를 계산하여 이때의 환경변수를 찾아내었다. 한편 해저면 잔향음신호는 표준화된 후방산란강도값들의 PDF를 만들어 그 분포양상을 분석하였다. 본 논문에서 사용된 알고리즘의 검증을 위해서는 보다 다양한 환경하에서 실시된 많은 음향괸측자료를 필요로 한다.

• The KSFM Journal of Fluid Machinery
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• v.16 no.3
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• pp.18-25
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• 2013

Recently the requirement of long-term mobile energy source for mobile robot or small-sized unmanned vehicle is highly increased, and the micro turbine generator(MTG) which is known to have high energy and power density is under development. MTG is designed to have air foil bearing and high speed rotor of which operating speed is 400,000rpm. In the development stage of high speed rotor and bearing, stability analysis for the full operational speed range is essential and the dynamic coefficients such as stiffness and damping coefficients of bearing depending on the rotational speed are required for that. Although perturbation method is usually used to identify the dynamic coefficients, it's not easy to give the perturbation to the high speed rotating rotor. In this study, we present the dynamic coefficients measurement system for air foil bearing which consists of electromagnets, gap sensors, high speed motor and controller. This measurement system can exert the sine sweep force to the rotor-bearing, measure the displacement of rotor and get FRF(Frequency response function) of rotor-bearing. The least square estimation method is applied to identify the dynamic coefficients of bearing from the measured frequency response at the different rpm and the identified dynamic coefficients for the wide rotational speed range are presented.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.134-143
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• 2006

Out of all types of motions the critical motions leading to capsize is roll. The dynamic amplification in case of roll motion may be large for ships as roll natural frequency generally falls within the frequency range of wave energy spectrum typical used for estimation of motion spectrum. Roll motion is highly non-linear in nature. Den are various representations of non-linear damping and restoring available in literature. In this paper an uncoupled non-linear roll equations with three representation of damping and cubic restoring term is solved using a perturbation technique. Damping moment representations are linear plus quadratic velocity damping, angle dependant damping and linear plus cubic velocity dependant damping. Numerical value of linear damping coefficient is almost same for all types but non-linear damping is different. Linear and non-linear damping coefficients are obtained form free roll decay tests. External rolling moment is assumed as deterministic with sinusoidal form. Maximum roll amplitude of non-linear roll equation with various representations of damping is calculated using analytical procedure and compared with experimental results, which are obtained form forced tests in regular waves by varying frequency with three wave heights. Experiments indicate influence of non-linearity at resonance frequency. Both experiment and analytical results indicates increase in maximum roll amplitude with wave slope at resonance. Analytical results are compared with experiment results which indicate maximum roll amplitude analytically obtained with angle dependent and cubic velocity damping are equal and difference from experiments with these damping are less compared to non-linear equation with quadratic velocity damping.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.229-250
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• 2022

Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.92-99
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• 2016

A wind turbine is controlled for the purpose of obtaining the maximum power below its rated wind speed. Among the methods of obtaining the maximum power, TSR (Tip Speed Ratio) optimal control and P&O (Perturbation and Observation) control are widely used. The P&O control algorithm using the turbine power and rotational speed is simple, but its slow response is a weak point. Whereas TSR control's response is fast, it requires the precise wind speed. A method of measuring or estimating the wind speed is used to obtain a precise value. However, estimation methods are mostly used, because it is difficult to avoid the blade interference when measuring the wind speed near the blades. Neural networks and various numerical methods have been applied for estimating the wind speed, because it involves an inverse problem. However, estimating the wind speed is still a difficult problem, even with these methods. In this paper, a new method is introduced to estimate the wind speed in the wind-power graph by using the turbine power and rotational speed. Matlab/Simulink is used to confirm that the proposed method can estimate the wind speed properly to obtain the maximum power.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.