• Journal of KSNVE
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• v.2 no.1
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• pp.49-59
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• 1992

The motion analysis of a translation device driven by a piezoelectric actuator is performed to identify the mechanics of impact drive mechanism and to find the maximum speed waveform. The translation device is modeled as a semidefinite two-degree-of-freedom system. The motion analysis includes effects of friction force between moving mass and contact surface, dynamics of voltage amplifier and piezoelectric elements, and hysteresis of piezoelectric actuator. Base on the model, simulation studies are carried out and then compared with experimental results. It is found that the error between moving distances obtained by analysis and experiment is less than 15% and that the actual motion of moving mass is well predicted by the analytical work, finally, precision positioning experiments are carried out by using a proximity sensor as a feedback sensor. Position control of moving mass is initiated by the maximum speed waveform and finely tuned by the scaled down waveform so that accurate positioning is accomplished within the resolution of the sensor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.472-477
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• 1996

This paper presents a new approachtothe design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.206-220
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• 2010

This paper proposes optimal control techniques for determining translational and rotational maneuvers that facilitate proximity operations and docking. Two candidate controllers that provide translational motion are compared. A state-dependent Riccati equation controller is formulated from nonlinear relative motion dynamics, and a linear quadratic tracking controller is formulated from linearized relative motion. A linear quadratic Gaussian controller using star trackers to provide quaternion measurements is designed for precision attitude maneuvering. The attitude maneuvers are evaluated for different final axis alignment geometries that depend on the approach distance. A six degrees-of-freedom simulation demonstrates that the controllers successfully perform proximity operations that meet the conditions for docking.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.433-440
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• 2012

Various studies to improve the physical abilities of the human have been steadily continued from the past to the present. Only recently such technology has been realized, and those are expected to replace or complement human beings in large part. In this paper, the current status of developed wearable robots is investigated and studies were conducted in order to apply the types of robots in industry spot. In order to apply wearable exoskeleton robot to industry which enhances human physical capability, driving range of the robot's degrees of freedom were selected by analyzing working motion, and augmentative exoskeleton structure design process is presented by analyzing require torque and power during selected working motion. At the end of this paper, the designed mock-up is introduced to validate the feasibility of designed robot.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.112-119
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• 2009

An automatic transmission of construction equipment is controlled by hydraulic and electronic system for doing in various functions like as shifting and operation. The shifting is operated by the engaged and disengaged clutch motion from hydraulic power. On the shifting process, suitable pressure control to the clutch is required for smooth shifting. Hydraulic control system in the automatic transmission is divided by the pilot control type and the direct control type greatly. The direct control type has an advantage than the pilot control type. Because the structure is simple, the design and the manufacture are having less troubles and the system can be maximized precision pressure control. However, the excellent performance proportional control valve should be used to achieve proper control-ability. In this study, the dynamic analysis model composing the automatic transmission and hydraulic system for forklift truck is presented to simulate the characteristics of hydraulic system about the direct control type. That model is verified the validity compared the results of the testing examination. Parameters of input signal are analyzed to reduce the output torque according to input control signal is affected in shifting characteristic.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.342-348
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• 1998

A majority of industrial robots are controlled by a simple joint servo control of joint actuators. In this type of control, the performance of control is greatly influenced by the joint interaction torques including Coriolis and centrifugal forces, which act as disturbance torques to the control system. As the speed of the robot increases, the effect of this disturbance torque increases, and hence makes the high speed - high precision control more difficult to achieve. In this paper, the joint disturbance torque of robots is analyzed. The joint disturbance torque is defined using the coefficients of dynamic equation of motion, and for the case of a 2 DOF planar robot, the conditions for the minimum and maximum joint disturbance torques are identified, and the effect of link parameters and joint variables on the joint disturbance torque are examined. Then, a solution to the optimal path placement problem is propose that minimizes the joint disturbance torque during a straight line motion. The proposed method is illustrated using computer simulation. The proposed solution method can be applied to a class of robots that are controlled by independent joint servo control, which includes the vast majority of industrial robots.

• 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.

• 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 Korean Society for Precision Engineering
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• v.27 no.12
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• pp.48-58
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• 2010

In this study, position tracking and force reflection control of a master-slave manipulator which will be used for handling objects contaminated by radioactivity has been addressed. Since available measurements concerning on dynamic motion of the master-slave manipulator are restricted, a simple constrained control structure was suggested. In the consideration of the uncertain dynamic behaviors of the slave manipulator which is dependent upon mass and shape of work pieces grasped and dynamic properties of the environment contacted, a simple structured sliding mode control was suggested to guarantee robustness with respect to parameter uncertainties and external disturbances. The proposed control was applied to a 1-DOF master-slave link system. The control performances were verified along with some computer simulation results.