• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.428-437
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• 2006

Many physical systems are hybrid in the sense that they have continuous behaviors and discrete phenomena. In control system with multiple models, switching strategy and stability of the closed-loop system under switching are very important issues. In this paper, a novel adaptive control scheme based on multiple parameter models is proposed to cope with a change in Parameters. Switching strategy guarantees the non-increase in the global control Lyapunov function if the estimation of Lyapunov function value converges. Least-square estimation is used to find the estimated value of the Lyapunov function. Switching and adaptation law guarantees the stability of closed-loop system in the sense of Lyapunov. Simulation results on anti-lock brake system are shown to verify the effectiveness of the proposed controller in view of a large change in system parameters.

• Structural Engineering and Mechanics
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• v.21 no.5
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• pp.507-518
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• 2005

In the shear-lag analysis of structures deterministic procedure is insufficient to provide complete information. Probabilistic analysis is a holistic approach for analyzing shear-lag effects considering uncertainties in structural parameters. This paper proposes an efficient and accurate algorithm to analyze shear-lag effects of structures with parameter uncertainties. The proposed algorithm integrated the advantages of the response surface method (RSM), finite element method (FEM) and Monte Carlo simulation (MCS). Uncertainties in the structural parameters can be taken into account in this algorithm. The algorithm is verified using independently generated finite element data. The proposed algorithm is then used to analyze the shear-lag effects of a simply supported beam with parameter uncertainties. The results show that the proposed algorithm based on the central composite design is the most promising one in view of its accuracy and efficiency. Finally, a parametric study was conducted to investigate the effect of each of the random variables on the statistical moment of structural stress response.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.1-18
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• 2000

In this paper, we study several parameter estimation methods used for autoregressive processes and compare them in view of forecasting. The least square estimation, least absolute deviation estimation, robust estimation are compared through Monte Carlo simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.45.5-45
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• 2002

In this paper, a quasi-deadbeat minimax estimation (QME) is proposed as a new class of time-domain parameter estimations for deterministic generic linear models. Linearity, quasi-deadbeat property, FIR structure, and independency of the initial parameter information will be required in advance, in addition to a new performance criterion of a worst case gain between the disturbances and the current estimation error. The proposed QME is obtained in a closed form by directly solving an optimization problem. The QME is represented in both a batch form and an iterative form. A fast algorithm for the suggested estimation is also presented, which is remarkable in view...

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.782-790
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• 2013

In this paper, we propose a better solution for swimming plans of an articulated underwater robot, Crabster, with a view point of biomimetics. As a biomimetic model of underwater organisms, we chose diving beetles structurally similar to Crabster. Various swimming locomotion of the diving beetle has been observed and sorted by robotics technology through experiments with a high-speed camera and image processing software Image J. Subsequently, coordinated patterns of rhythmic movements of the diving beetle are reproduced by simple control parameters in a parameter space which make it easy to control trajectories and velocities of legs. Furthermore, a simulation was implemented with an approximated model to predict the motion of the robot under development based on the classified forward and turning locomotion. Consequently, we confirmed the applicability of parameterized leg locomotion to the articulated underwater robot through the simulated results by the approximated model.

• Journal of Mechanical Science and Technology
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• v.14 no.4
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• pp.393-400
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• 2000

In this paper, a new algorithm for noninteracting control system design is proposed and applied to ship propulsion system control. For example, if a ship diesel engine is operated by consolidated control with controllable pitch propeller (CPP), the minimum fuel consumption is achieved satisfying the demanded ship speed. For this, it is necessary that the ship is operated on the ideal operating line which satisfies the minimum fuel consumption, and the both pitch angle of CPP and throttle valve angle are controlled simultaneously. In this context of view, this paper gives a controller design method for a ship propulsion system with CPP based on noninteracting control theory. Where, linear matrix inequality (LMI) approach is introduced for the control system design to satisfy the given $H_{\infty}$, constraint in the presence of physical parameter perturbation and disturbance input. To the end, the validity and applicability of this approach are illustrated by the simulation in the all operating ranges.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• Journal of Advanced Marine Engineering and Technology
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• v.11 no.3
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• pp.61-69
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• 1987

The PID controller is one of the most popular devices for control systems and the adjustment of its parameters has been generally accomplished by semi-empirical rules and has been considered only in the view of improvement of the control performance. But in modern control theory, a quadratic form is introduced as a criterion function which considers not only to improve quality of control but also to save energy required for the control. In this paper, authors propose a method of the parameter adjustment of the PID controller by means of maximum principle minimizing the quadratic criterion function and establish a link between the conventional parameter adjustment method and the technique of the modern optimal control theory in the design of a PID controller.

• Journal of the Korean Society of Industry Convergence
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• v.2 no.2
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• pp.181-186
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• 1999

For an unmanned machining system, the control and disposal of chips is one of the most serious problems at present. In order to perform chip control, feed/land length($F_L$) was introduced, and using this parameter, the cutting performance and chip breaking characteristics of groove-type and the land -angle-type chip formers were assessed. The specific cutting energy consumed and the shape of broken chips with its breaking cycle time were evaluated to find out the ranges of $F_L$ value where efficient cutting and effective chip breaking could be achieved. The C type chip was found to be the most preferable from the view point of cutting efficiency.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.227-237
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• 2004

In this paper we presented a Bayesian inference approach for estimating the location and scale parameters of the lognormal distribution using iterative Gibbs sampling algorithm. We also presented estimation of location parameter by two non iterative methods, importance sampling and weighted bootstrap assuming scale parameter as known. The estimates by non iterative techniques do not depend on the specification of hyper parameters which is optimal from the Bayesian point of view. The estimates obtained by more sophisticated Gibbs sampler vary slightly with the choices of hyper parameters. The objective of this paper is to illustrate these tools in a simpler setup which may be essential in more complicated situations.