• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1723-1728
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• 2005

This article describes the fuzzy control of the 3-dimensional motion of the container cranes used in dockside container terminals. The container is suspended by four flexible cables via spreader, and due to the disturbances such as the wind and acceleration of cranes, the container undergoes translational(sway) and rotational position errors. And due to the uncertainty of weight and rotational inertia, accurate position control of container crane is difficult to realize. This paper, based on the analysis of 3-dimensional dynamics of container moving systems, describes the design of the fuzzy controller, which does not require the computation time to optimize the distribution of cable tension. The developed controller is shown effective in controlling the container position in the presence of gust and parameter uncertainties.

• 한국기계연구소 소보
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• s.15
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• pp.5-17
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• 1985

Dynamics of railway vehicles are strongly influenced by the wheel/rail contact forces. Wheel/rail contact geometric characteristics are important parameters to determining wheel/rail contact forces. In general, geometric relations between wheel and rail are represented by nonlinear functions of the wheelset lateral excursion and the relative yaw angle. There are some analytical and experimental studies to show the influences of the wheelset lateral displacement on wheel/rail geometric relations. Recently radial steering bogie which is designed to have flexible yaw motions of wheelsets was developed to improve curve negotiation performance. The radial steering bogie makes it important problem to study the effects of wheelset yaw motion on wheel/rail geometric relations. This paper describes the method to analyze 3-dimensional wheel/rail contact geometry considering wheelset yaw motion and describes also some computer simulation results.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.255-260
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.4
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• pp.555-563
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• 2001

Support dynamics are often important in rotordynamic analyses. It may well happen in real situation of machines such as centrifugal pumps or turbines operating on flexible structure. This paper presents the applications of the impedance coupling method and the improved rotor model for including the support effects on the interaction with the rotor. The impedance coupling techniques are based on the FRFs of each substructure. Its dynamic stiffness matrix can be assembled to generate the system matrix, which satisfy the constraint conditions in the connection coordinates. And, the improved rotor uses the simplified spring-mass models as support properties. The equivalent support models are directly incorporated into the finite element rotor model. To verify the suggested analytical procedures, the results are compared to those of the pump system.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1938-1948
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• 2003

This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• 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.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.15 no.2
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• pp.97-122
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• 2011

Fluid dynamics driven by pumping without valves (valveless pumping) shows interesting physics. Especially, the driving function to generate valveless pump mechanism is one of important factors. We consider a closed system of valveless pump which consists of flexible tube part and stiffer part. Fluid and structure (elastic tube) interaction motions are generated by the periodic compress-and-release actions on an asymmetric location of the elastic loop of tubing. In this work, we demonstrate how important the driving forcing function affects a net flow in the valveless circulatory system and investigate which parameter set of the system gives a more efficient net flow around the loop.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.53-60
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• 2001

This paper considers a modeling for the MIMO magnetic bearing system. The rotor is flexible and has a complex shape. To obtain the nominal plant transfer functions, we perform a numerical analysis by using the finite element method(F.E.M.) for the rotor's dynamics, and make a nominal model by reducing the modes from the results. And, we have experimented on the frequency response by a closed-loop identification method, and compared it with the simulation's result on the closed-loop control system.