• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.947-955
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• 2004

This paper is concerned with a mixed control with aerodynamic fin and side thrust control applied to an agile missile using a dynamic inversion and a time-varying control technique. The nonlinear dynamic inversion method with the weighting function allocates the desired control inputs(aerodynamic fin and side thrust control) to achieve a reference command, and the time-varying control technique plays the role to guarantee the robustness for the uncertainties. The proposed schemes are validated by nonlinear simulations with aerodynamic data.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.11
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• pp.3649-3654
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• 1996

A transient hydraulic flow rate computation scheme is described here so that the transient hydraulic flow rate can be determined using the dynamic pressure measurements at the ends of a straight flow line with a dynamic model of the hydraulic line. This method can be applied to determine the orifice ares of high response valve. Simulation results indicate that the method is relatively robust to realistic levels of uncertainties in the fluid properties.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

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 n 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• 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.

• Coupled systems mechanics
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• v.4 no.1
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• pp.19-36
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• 2015

Modelling and analysis of a brick masonry building involves uncertainties like modelling assumptions and properties of local material. Therefore, it is necessary to perform a calibration to evaluate the dynamic properties of the structure. The response of the finite element model is improved by predicting the parameter by performing linear dynamic analysis on experimental data by comparing the acceleration. Further, a nonlinear dynamic analysis was also performed comparing the roof acceleration and damage pattern of the structure obtained analytically with the test findings. The roof accelerations obtained analytically were in good agreement with experimental roof accelerations. The damage patterns observed analytically after every shock were almost similar to that of experimental observations. Damage pattern with amplification in roof acceleration exhibit the potentiality of earthquake resistant measures in brick masonry models.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.126-135
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• 1997

A sensorless motion planner which succeeds in grasping a polygonal part firmly into a desired orientation has been developed through the dynamic analysis. The analytical results on the impact process with friction are used for modeling the contact motionduring the parallel-jaw grasp operation, which is com- posed of the pushing and the squeezing process. The developed planner succeeds in grasping a part into a specified orientation in the face of uncertainties of initial position and orientation of the part, motion direction of the finger, and the physical parameters such as the coefficients of friction and restitution. The motion planner has been fully implemented into a viable package on the computer system, and verified experimentally. The motion of parts is recorded using a high-speed video camera, and then compared to the results of the planner and the graphic simulation results that illustrate the simulated motion of the grasp operation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1289-1294
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• 2010

In this paper, a new discrete integral static output feedback variable structure controller based on the a new integral dynamic-type sliding surface and output feedback discrete version of the disturbance observer is suggested for the control of uncertain linear systems. The reaching phase is completely removed by introducing a new proposed integral dynamic-type sliding surface. The output feedback discrete version of disturbance observer is presented for effective compensation of uncertainties and disturbance. A corresponding control with disturbance compensation is selected to guarantee the quasi sliding mode on the predetermined integral dynamic-type sliding surface for guaranteeing the designed output in the integral dynamic-type sliding surface from any initial condition for all the parameter variations and disturbances. Using discrete Lyapunov function, the closed loop stability and the existence condition of the quasi sliding mode is proved. Finally, an illustrative example is presented to show the effectiveness of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.197-200
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• 1996

This paper considers feedback error learning neural networks for robot manipulator control. Feedback error learning proposed by Kawato [2,3,5] is a useful learning control scheme, if nonlinear subsystems (or basis functions) consisting of the robot dynamic equation are known exactly. However, in practice, unmodeled uncertainties and disturbances deteriorate the control performance. Hence, we presents a robust feedback error learning scheme which add robustifying control signal to overcome such effects. After the learning rule is derived, the stability is analyzed using Lyapunov method.