• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.1-2
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• 1994

With the prevalence of computers in modern organizations, simulation is receiving more atention as an effectvie decision -making tool. Simualtion is a computer-based numerical technique which uses mathmatical and logical models to approximate the behaviror of a real-world system. However, iptimization of synamic stochastic systems often defy analytical and algorithmic soluions. Although a simulation approach is often free fo the liminting assumption s of mathematical modeling, cost and time consiceration s make simulation the henayst's last resort. Therefore, whenever possible, analytical and algorithmica solutions are favored over simulation. This paper discussed the issues and procedrues for using simulation as a tool for optimization of stochastic complex systems that are dmodeled by computer simulation . Its emphasis is mostly on issues that are speicific to simulation optimization instead of consentrating on the general optimizationand mathematical programming techniques . A simulation optimization problem is an optimization problem where the objective function. constraints, or both are response that can only be evauated by computer simulation. As such, these functions are only implicit functions of decision parameters of the system, and often stochastic in nature as well. Most of optimization techniqes can be classified as single or multiple-resoneses techniques . The optimization of single response functins has been researched extensively and consists of many techniques. In the single response category, these strategies are gradient based search techniques, stochastic approximate techniques, response surface techniques, and heuristic search techniques. In the multiple response categroy, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphica techniqes, direct search techniques, constrained optimization techniques, unconstrained optimization techniques, and goal programming techniques. The choice of theprocedreu to employ in simulation optimization depends on the analyst and the problem to be solved. For many practival and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computersimulation is one of the most effective means of studying such complex systems. In this paper, after discussion of simulation optmization techniques, the applications of above techniques will be presented in the modeling process of many flexible manufacturing systems.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.117-123
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• 2001

In a modern control field, a control engineer who has theoretical backgrounds with some practical knowledge is demanded. That is to say, an engineer who can understand and operate the various parts such as modeling, simulation, system analysis, signal processing, statistics, and hardware is required. In order to prove the theoretical backgrounds and operate various hardwares, a lot of experimental devices for students are designed in universities. Since the conventional experimental devices are manufactured abroad and the prices of the devices are too high, it is difficult to have. If a low cost experimental device can be developed, it will be very useful for a control engineering education. In Ibis paper, an experimental rig which has two control inputs and three sensor outputs to control the end point of a flexible beam is designed and manufactured. This rig can be used for a control field education.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.2
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• pp.81-91
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• 1992

A control methodology for suppressing the elastodynamic responses of high-speed flexible linkage mechanisms is presented by adopting the concept of smart structures featuring piezoelectric films. The dynamic modeling of the proposed mechanism is accomplished by employing a finite element formulation which accounts for dynamic motion in both inertial and elastic coordinates. The dynamics of piezoelectric actuators and sensors bonded on the original flexible structure are developed for one-dimensional beam in conjunction with the modal analysis. The linear optimal controller which consists of a feedback control law and a Luenberger observer is employed. Numerical simulation is performed to evaluate the improvement of elastodynamic responses.

• Structural Engineering and Mechanics
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• v.4 no.3
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• pp.277-301
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• 1996

A finite element model of a beam element with flexible connections is used to investigate the effect of the randomness in the stiffness values on the modal properties of the structural system. The linear behavior of the connections is described by a set of random fixity factors. The element mass and stiffness matrices are function of these random parameters. The associated eigenvalue problem leads to eigenvalues and eigenvectors which are also random variables. A second order perturbation technique is used for the solution of this random eigenproblem. Closed form expressions for the 1st and 2nd order derivatives of the element matrices with respect to the fixity factors are presented. The mean and the variance of the eigenvalues and vibration modes are obtained in terms of these derivatives. Two numerical examples are presented and the results are validated with those obtained by a Monte-Carlo simulation. It is found that an almost linear statistical relation exists between the eigenproperties and the stiffness of the connections.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.337-346
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• 2004

The control scheme using fuzzy modeling and Parallel Distributed Compensation (PDC) concept is proposed to provide asymptotic tracking of a reference signal for the flexible joint manipulators with uncertain parameters. From Lyapunov stability analysis and simulation results, the developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop multi-input/multi-output system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.101-109
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• 1997

An analytical procedure on the base of the substructure synthesis and assumed modes method is developed to investigate the flexibility effect of bladed disk assembly on vibrational modes of flexible rotor system. In modeling the system, Coriolis forces, gyroscopic moments, and centrifugal stiffening effects are taken into account. The coupled vibrations between the shaft and bladed disk are then extensively investigated through the numerical simulation of simplified models, with varying the shaft rotational speed and the pretwist and stagger angles of the blade. It is found that the Coriolis and inertia forces and the inertia torque, which are induced by the one nodal diameter modes of the bladed disk and vary depending upon the stagger and pretwist angles, lead to the coupled motions of the shaft and the bladed disk.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.56-60
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• 1996

In most dynamic manufacturing environments today, systems and processes are constantly changing. Simulation tools are required that can accurately model the system in detail, but still be easy to use, and allow rapid model redevelopment to react quickly for system changes. An object-oriented simulation modeling environment is presented to provide flexible modeling capabilities for simulation. Also, when simulating an assembly system, a large number of factors must be considered. Because of such complexities, simulation has been used as the primary method in designing, planning and analyzing. In this paper, the dynamic manufacturing environment is discussed for the assembly system. Also, an application method of simulation tools is presented with the experimental data from the automobile manufacturing shop to improve the productivity effectively.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.45-54
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• 2010

The inherent complexity of semiconductor fabrication processes makes it hard to solve well-known job scheduling problems in analytical ways, which leads us to rely practically on discrete event modeling simulations to learn the effects of changing the system's parameters. Meanwhile, unpredictable disturbances such as machine failures and maintenance diminish the productivity of semiconductor manufacturing processes with fixed scheduling policies; thus, it is necessary to adapt job scheduling policy in a timely manner in reaction to critical environmental changes (disturbances) in order for the fabrication process to perform optimally. This paper proposes an adaptive job control framework for a wafer fabrication process in a control system theoretical approach and implements it based on a DEVS modeling simulation environment. The proposed framework has the advantages in view of the whole systems understanding and flexibility of applying new rules compared to most ad-hoc software approaches in this field. Furthermore, it is flexible enough to incorporate new job scheduling rules into the existing rule set. Experimental results show that this control framework with adaptive rescheduling outperforms fixed job scheduling algorithms.

• Journal of the Korea Society for Simulation
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• v.9 no.1
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• pp.39-54
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• 2000

Presented in this paper is a modeling and simulation methodology for 3 dimensional man-made systems. Based on DEVS(discrete event system specification) formalism[13], we propose GK-DEVS (geometrical and kinematic DEVS) formalism to describe the geometrical and kinematic structure and continuous state dynamics. To represent geometry and kinematics, we add a hierarchical structure to the conventional atomic model. In addition, we employ the "empty event" and its external event function for continuous state changing. In terms of abstract simulation algorithm[13], the simulation method of GK-DEVS, named GK-Simulator, is proposed for combined discrete-continuous simulation. Using GK-DEVS, the simulation of an FMS(flexible manufacturing system) consisting of a luring machine, a 3-axis machine and a RGV-mounted robot has been peformed.en peformed.