• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.389-391
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• 1996

A Hybrid technique is introduced in this paper for a manipulator with 2 DOF flexible links. The manipulator dynamics plus the actuator dynamics is controlled by taking force feedback for the end-effector of the link 2 while controlling the position of link I to control the position of the end-effector.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.460-463
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• 1995

The present paper studies a robot manipulator's contact tasks on the uncertain flexible objects. The flexible object's distributed parameter model is approximated into a lumped "position state-varying" model. By using the well-known nonlinear feedback compensation, the robot's control space is decomposed into the position control subspace and the object's torque control subspace. The optimal state feedback is designed for the position loop, and the robot's contact force is controlled through controlling the resultant torque on the object using model-reference simple adaptive control. Experiments of a PUMA robot interacting with an aluminum plate show the effectiveness of this control approach. approach.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.369-373
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• 1992

Force control of a planar two-link structurally flexible robotic manipulator is considered in this study. The dynamic model is obtained by using the extended Hamilton's principle and the Galerkin criterion. A method is pressented toobtain the linearized equations of motion in Cartesian space for use in designing the control system. The approachto solving the control problem is to use feedforward and feedback control torques. The feedforward torques maneuver the flexible manipulatro along a nominal trajectory and the feedback torques minimize any deviations from the nominal trajectory. The linear quadratic Gaussian/loop transfer recovery (LQG/LTR) design methodology is explotied to design a robust feedback control system that can handle modeling errors and sensor noise, and operates on Cartesian space trajectory errors. The Lqg/LTR compenstaor together with a feedforward ollp is used to control the flexible manipulator. Simulated results are presented for a numerical example.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.261-262
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• 2012

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.50-59
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• 1998

This paper presents stabilization and adaptive control of flexible single link robot manipulator system by self-recurrent neural networks that is one of the neural networks and is effective in nonlinear control. The architecture of neural networks is a modified model of self-recurrent structure which has a hidden layer. The self-recurrent neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by feedback-error learning algorithm. When a flexible manipulator is rotated by a motor through the fixed end, transverse vibration may occur. The motor toroque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipuators so that it is arresed as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large changes in configuration common to robotic tasks requires dynamic models that describe both the rigid body motions, as well as the flexural vibrations. Therefore, a dynamic models for a flexible single link robot manipulator is derived, and then a comparative analysis was made with linear controller through an simulation and experiment. The results are proesented to illustrate thd advantages and imporved performance of the proposed adaptive control ove the conventional linear controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.106-116
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• 1998

A position control algorithm of a flexible manipulator is studied. The proposed algorithm is based on an ACFAC(Automatic Constructed Fuzzy Adaptive Controller) system based on the neural network learning algorithms. The proposed system learns membership functions for input variables using unsupervised competitive learning algorithm and output information using supervised outstar learning algorithm. ACFAC does not need a dynamic modeling of the flexible manipulator. An ACFAC is designed that the end point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by error, velocity and variation of error. Simulation and experiment results show a robustness of ACFAC compared with the PID control and neural network algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.185-191
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• 1993

A flexible nanipulator can move in the high speed even with the small driving torque. The dynamic equations of flexible manipulator whichinclude 2 vibrationalmodes are derived using the clamped-free boundarycondition. Simulation results of the 6th order modelare well matched with experimental results. The hub angle of the flexible manipulator can be controlled without vibration of beam by the feedback of both hub angle and strain. The overshoot of the hub angle in the step resonse is reduced without sacrificing the rise time using the cycloidal function instead of the step function as the reference input.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.266-271
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• 1992

This paper presents a new stable composite control law for the flexible joint robot manipulators, which incorporate the additional stabilizing control law with sliding property. The singularly perturbated models include inertia moments functions of the deformations of actuator. The newly defined fast controller variable is computed from the corrected reduced-order model without additional computational loads. The simulations for 2 DOF flexible joint manipulator show that the proposed schemes are more stable than conventional one, and especially effective for the manipulator with high joint-flexibilities.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.428-433
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• 1997

This paper presents a new control strategy for the position and force control of flexible manipulators. The governing equation of motion of a two-link flexible manipulator which features piezoceramic actuators bonded on each flexible beam is derived via Hamilton's principle. The control torque of the motor to command desired position and force is determined by a sliding mode controller on the basis of the rigid-mode dynamics. In the controller formulation, the sliding mode controller with perturbation estimation(SMCPE) is adopted to determine appropriate control gains. The SMCPE is then incorporated with the fuzzy technique to mitigate inherent chattering problem while maintaining the stability of the system. A set of fuzzy parameters and control rules are obtained from a relation between estimated perturbation and actual perturbation. During the commanded motion, undesirable oscillation is actively suppressed by applying feedback control voltages to the piezoceramic actuators. These feedback voltages are also determined by the SMCPE. Consequently, accurate force and position control of a two-link flexible manipulator are achieved. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control methodology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.342-345
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• 1995

This paper describes the design process and the experimental results of a fuzzy logic controller to control the tip position of a fixible-link manipulator, directly driven by a AC motor, with a large payload. The joint angle fuzzy logic controller is designed without a costly nonlinear system analysis of the flexible manipulator and the AC motor drive system. The state variables for the fuzzy logic controller are joint angle, joint velocity, link deflection, and link deflection velocity. The simulation and experimental results show that the joint position control is not satisfactory when the controller is designed under the assumption of no link flexibility and that stable joint position control and link vibration suppression can be cahieved with the fuzzy logic controller suggested in this paper.