• 전기의세계
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• v.26 no.6
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• pp.48-54
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• 1977

The object of this work is to study the optimal control strategy of constant speed characteristics for a D.C control motor under influence of disturbance. In the course of the analysis, the linearization and time invariance schemes on motor dynamics are presumed throughout under certain prescribed conditions and the performance measure for optimality is assumed to be quadratic in state and the control effort, with the initial and final time specified. When the motor speed is deviated from a stationary operating point by any external disturbance, the optimal continuous feedback control law is investigated by the application of the calculus of variation and realizability of the required control meachanism is suggested. Finally, the comparative study of the speed reasponses of the motor, with and without the optimal control effort is also presented to confirm the obtained results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.112-112
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• 2000

The aim of this paper is to design a two degree-of-freedom H$_{\infty}$ controller for lateral control of the vehicle. The object of this controller is to track the centerline of the reference lane. The controller is splited into two parts, feedback and prefilter. The feedback part is for both robust stability and disturbance attenuation, while the prefilter is for improving the robust tracking properties of closed loop system. This paper is consist of preface, background theory, dynamics of vehicle, controller design and computer simulation.ter simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.414-419
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• 1994

In recent years, there has been an increasing intest in control of active automotive suspension systems with a goal of improving the ride comfort and safety. Many approaches for these purposes have used linearized models of the suspension's dynamics, allowing the use of linear control theory. However, the linearized model does not well descriibe the actual system behavior which is inherently nonlinear. The object of this study is to develop a neuro controlled active suspension for the ride quality improvement. After obtaining active control law using optimal control theory, we use the artificial neural network to train the neuro controller to learn the relation of road input and control force. Form the numerical results, we found that back propagation learning does show good pattern matching and vertical acceleration of the driver's seat and sprung mass.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.5 no.1
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• pp.57-64
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• 1991

The paper considers a distributed adaptive control technique for Industrial Robots which contribute to the factory automation. The control object is to tracking for a desired trajectories under various load conditions, rapidly against load variation. These control techniques divided whole system into subsystems which is controlled with the Nominal and Adaptational controllers. And also the asymptotic stability of these substem was proved. Simulation results shown that the proposed techniques was feasible in spite of nonlinear dynamics of robot manipulator and payload variations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.3
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• pp.25-34
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• 1992

This paper proposes a Self-Tuning control algorithm for tracking the reference trajectory by measuring the end-point of robot manipulator whose links are light and flexible, and the performance of it is tested through the computer simulation. As an object of system, a flexible robot manipulator with two-links is considered and an assumed mode shape method including gravity force is adopted to analyze the vibration modes for each links and dynamics equation is derived. The controller is designed as a combined form which consists of dynamic feedforward compensator and self-tuning feedback controller. The one supplies nominal torque and the other supplies variational torque to manipulator. Apart from the, K-incremental predictor is also proposed in order to eliminate the offset error. and it shows that the result of simulation adapted well to load change and rapid velocity.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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• pp.217-223
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• 1991

Most common applications of neural networks to control problems are the automatic motor controls using the artificial perceptual function. These control mechanisms are similar to those of the intelligent and pattern recognition control of an adaptive method frequently performed by the animate nature. In this paper, the pole-balancing problem is selected as the control object and an actual cart-pole controller is implemented by a computer interfacing and demonstrated as motor control using the reinforcement learning rule. In the experiment, given a change of the main parameters of cart-pole dynamics, a comparison is made between the LQR scheme and neural network method. The neural network method exhibits a more effecftive control action in a real situation having a large uncertainty than the LQR scheme.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.980-983
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• 1996

This paper presents the method of determining state feedback gains of XPTOS for disk drive servomechanism based BESSEL filter prototype. A typical disk drive actuator can be modeled as second order dynamics for low frequencies. However, the response at higher frequencies shows resonant behavior which cannot be easily modeled. XPTOS consists of the nonlinear control region and the linear control region. In the linear control region, the poles of a second order nominal model of plant must be properly relocated by pole placement technique to attenuate resonant modes at high frequency and to attain minimum time state transition. It is difficult to select position to satisfy this object because velocity feedback gain is subjected to position feedback gain in XPTOS. Here poles of BESSEL filter prototype are selected to determine state feedback gains of XPTOS. Simulation results for disk drive servomechanism using XPTOS having state feedback gains by the proposed method are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1738-1756
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• 2020

To improve the accuracy and realism of the virtual surgical simulation system, this paper proposes an optimized mass-spring model with shape restoration ability based on volume conservation to simulate soft tissue deformation. The proposed method constructs a soft tissue surface model that adopts a new flexion spring for resisting bending and incorporates it into the mass-spring model (MSM) to restore the original shape. Then, we employ the particle swarm optimization algorithm to achieve the optimal solution of the model parameters. Besides, the volume conservation constraint is applied to the position-based dynamics (PBD) approach to maintain the volume of the deformable object for constructing the soft tissue volumetric model base on tetrahedrons. Finally, we built a simulation system on the PHANTOM OMNI force tactile interaction device to realize the deformation simulation of the virtual liver. Experimental results show that the proposed model has a good shape restoration ability and incompressibility, which can enhance the deformation accuracy and interactive realism.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.415-420
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• 2020

Crowd flows occur in metropolitan railway transit stations, terminals, multiple buildings, and stadiums and are important in ensuring the safety as well as smooth flow of pedestrians in these facilities. In this study, the author developed a new computational analysis method for crowd flow dynamics and applied it to models of transit connecting paths. Using the analysis method, the potential value of the exit was assigned the smallest value, and the potential value of the surrounding grids gradually increased to form the overall potential map. A pathline map was then constructed by determining the direction vector from the grid with large potential value to the grid and small potential. These pathlines indicate basic routes of passenger flow. In all models of the analysis object, the pedestrians did not move to the first predicted shortest path but instead moved using alternative paths that changed depending on the situation. Even in bottlenecks in which pedestrians in both directions encountered each other, walking became much smoother if the entry time difference was dispersed. The results of the analysis show that a method for reducing congestion could be developed through software analysis such as passenger flow analysis without requiring hardware improvement work at the railway station.

• Journal of Advanced Marine Engineering and Technology
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• v.41 no.3
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• pp.258-268
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• 2017

In this study, we aim to converge a technology for analyzing the hydraulic circuit of a loading arm with an- other one for analyzing multi-body dynamics by utilizing analysis software SimulationX. Further, this study intends to overcome the limitations of the existing technology for analyzing a hydraulic circuit with a variation at the rotation center of the moving mass and the difficulty of incorporating the behavior in a gravity field. First, the specifications of the hydraulic circuit components were reflected in an analysis model to secure reliability. Hydraulic circuit modeling was then performed using a single analysis model with a verified reliability. Subsequently, the multi-body system (MBS) model of the loading arm was formed. Finally, the analysis model of the hydraulic circuit and the MBS model were converged to check if the circuit analysis result was exactly reflected in the MBS model. The convergence analysis model has development cost-saving effect because it is capable of predicting the dynamic behavior of an object without the prototype.