• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.756-765
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• 2001

An effective dexterous motion control method of redundant robot manipulators based on neural optimization network is proposed to satisfy multi-criteria such as singularity avoidance, minimizing energy consumption, and avoiding physical limits of actuator, while performing a given task. The method employs a neural optimization network with parallel processing capability, where only a simple geometric analysis for resolved motion of each joint is required instead of computing of the Jacobian and its pseudo inverse matrix. For dexterous motion, a joint geometric manipulability measure(JGMM) is proposed. JGMM evaluates a contribution of each joint differential motion in enlarging the length of the shortest axis among principal axes of the manipulability ellipsoid volume approximately obtained by a geometric analysis. Redundant robot manipulators is then controlled by neural optimization networks in such a way that 1) linear combination of the resolved motion by each joint differential motion should be equal to the desired velocity, 2) physical limits of joints are not violated, and 3) weighted sum of the square of each differential joint motion is minimized where weightings are adjusted by JGMM. To show the validity of the proposed method, several numerical examples are illustrated.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.648-653
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• 1993

This paper presents an nonlinear observer scheme for flexible joint robot manipulators. This nonlinear observer scheme is based on the sliding mode method. Sliding controllers have recently been shown to feature excellent robustness and performance properties for specific classes of nonlinear tracking problems. Dynamic equations of flexible joint robot manipulators are derived from the Euler-Lagrange equations by forming the corresponding Lagrangian. Simulation results are presented to show the validness of the proposed nonlinear observer scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.889-894
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• 1993

This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.597-600
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• 1994

A Robot system to realize a painting using a writing brush is explained here. Based on the three-dimensional data about the target china, the movements of the writing brush is determined. The movement is realized by the movement of two robot manipulators which move coordinatedly. Experimental results reveals the applicability of one system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.921-925
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• 1987

This paper presents the recent findings for collision avoidance of two manipulators in addition to the results shown in Lee [4]. The collision situation we assume here is that the prespecified final time $K_{f}$ and the prespecified path of one robot can be modified for the purpose of collision avoidance with the other robot. The collision avoidance problem is resolved into three independent categories for a systematic approach.h.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.893-898
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• 1988

This paper presents the recent findings for collision avoidance of two manipulators in terms of motion level modifications. The collision situation we assume here is that the prespecified final time Kf and the prespecified path of one robot can be modified for the purpose of collision avoidance with the other robot. The collision avoidance problem is resolved into three independent categories for a systematic approach.

• Journal of Electrical Engineering and information Science
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• v.3 no.1
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• pp.36-44
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• 1998

In this paper, a robust adaptive sliding mode control algorithm for accurate trajectory tracking of robot manipulators is proposed, with unknown parameters being estimated on-line. The controller is designed based on a Lyapunov method, which consists of adaptive feed-forward compensation part and a discontinuous control part. It is shown that, in the presence of the uncertainty and the disturbances arising from the actuator or some other causes, the tracking errors is bound to converge to zero asymptotically. An illustrative example is given to demonstrate the results of the propose method.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.344-346
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• 1992

In this paper a robust hybrid control algorithm for n-link nonredundant robot manipulators is proposed. This scheme includes an estimation law for the upper bound on the uncertainty such that robust control input is updated as a function of the estimated upper bound. The uniform ultimate boundedness of the tracking error is generated by the Lyapunov based theory.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.37.5-37
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• 2001

A robust control for robot manipulators actuated by induction motors using neural networks(NNs) is considered. The control is designed to compensate for nonlinear dynamics associated with the mechanical subsystem and the electrical subsystems only with the measurements of link position, link velocity and stator winding currents. Two-layer NNs are used to approximate unknown functions occurring from parameter variation during backstepping design process. Specially, through the use of nonlinear observers for rotor flux, observed backstepping controller is designed to achieve uniform ultimately bounded link position tracking of the given reference signal ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.155.5-155
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• 2001

The robust predictive control law which use the bound estimation is proposed for uncertain robot manipulators. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about model, it´s an important tend to design a robust control law that will guarantee the desired performance of the manipulator under uncertain elements. In the preceeding work, the robust predictive control law was proposed. In this work, we propose a class of robust predictive control of manipulators with the bound estimate technique and fe stability based on Lyapunov function is presented.