• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.1-162
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• 2001

In this paper, the adaptive fuzzy system is used as an adaptive approximator for robot nonlinear dynamic. A theoretical justification for the adaptive approximator is proving that if the representive point(RP or switching function) and its derivative in sliding mode control are used as the inputs of the adaptive fuzzy system, the adaptive fuzzy system can approximate robot nonlinear dynamics in the neighborhood of the switching surface. Thus the fuzzy controller design is greatly simplified and at the same time, the fuzzy control rule can be obtained easily by the reaching condition. Based on this, a new method for designing an adaptive fuzzy control system based on sliding mode is proposed for the trajectory tracking control of a robot with unknown nonlinear dynamics.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.478-482
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C50) for robotic manipulators to achieve trajectorytracking angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adapation laws are derived from the improved second stability analysis based on the indirect adaptive control theory.l The proposed control scheme is simple in structure, fast in computation, an suitable for implementation of real-time control. Moreover, this scheme does not requre an accurate dynamic modeling, nor values of manipulator paramenters and payload Performance of the adaptive controller is illustrated by exeperimental results for a SCARA robot.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.406-410
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• 2008

This paper presents a new robot calibration algorithm with joint stiffness parameters for the enhanced positioning accuracy of industrial robot manipulators. This work is towards on-going development of an industrial robot calibration software which is able to identify both the kinematic and non-kinematic robot parameters. In this paper, the conventional kinematic calibration and its important considerations are briefly described first. Then, a new robot calibration algorithm which simultaneously identifies both the kinematic and joint stiffness parameters is presented and explained through a computer simulation with a 2 DOF manipulator. Finally, the developed algorithm is implemented to Hyundai HX165 robot and its resulting improvement of the positioning accuracy is addressed.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1223-1232
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• 2004

We present a new technique to the design and real-time implementation of fuzzy control system basedon digital signal processors in order to improve the precision and robustness for system of industrial robot in this paper. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a Fuzzy Logic Controller, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult Self-Organizing Fuzzy Controller is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed Self-Organizing Fuzzy Controller scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.16-19
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• 1996

In this paper, a sliding mode control scheme that guarantees the smoothness of the control signal and the exponential error convergence is proposed for robot manipulators. The proposed method inserts a low pass filter (LPF) in front of the plant, and the virtual controller is designed for the virtual plant - the combination of the LPF and the robot manipulator. The virtual control signal contains high frequency components because of a switching function. The real control signal, however, always shows a smooth curve since it is an output of the LPF. In addition to the smoothness of the control signal is always assured, the overall system is in the sliding mode at all times, that is, its performance is always invariant under the existence of parameter uncertainties and external disturbances. The closed-loop system is shown to be globally exponentially stable.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.22-29
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• 2004

This paper studies the coordinated trajectory control of an excavator as a kind of robotic manipulators driven by hydraulic actuators. Hydraulic robot system has many non-linearity in dynamics and kinematics, and strong coupling among joints(or hydraulic cylinders). This paper proposes a combined controller frame of the adaptive robust control(ARC) and the sliding mode control(SMC) for the trajectory tracking control of the excavator to preserve the advantages of the both methods while overcoming their drawbacks, namely, asymptotic stability of adaptive system for parametric uncertainties and guaranteed transient performance of sliding mode control for both parametric uncertainties and external disturbance. The suggested control technique is applied for the tracking of a straight-line motion of end-effector of manipulators, and through computer simulations, its trajectory tracking performances and the robustness to payload variation and uncertainties are illustrated.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.393-402
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• 1990

An iterative learning contol method is presented for a class of linear periodic systems, in which a parameter estimator of the system together with an inverse system model is utilized to generate the control signal at each iteration. A convergence proof is given and two numerical examples are illustrated to show the validities of the algorithm. In particular, it is shown that the method is useful for the continuous path control of robot manipulators.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.183-188
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• 1994

A passivity-based adaptive controller for robots executing fine motion tasks is proposed. The robot dynamics is modelled such that it is subject to holonomic constraints and hence it can be treated as a particular case of constrained motion tasks. Energy-motivated stability analysis is used to conclude the asymptotic stability. Remarks regarding the structure of the controller are given. A computer simulations study is presented and a robust constraint stabilization algorithm is also proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.936-939
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• 1996

In this paper, two specially designed associative mapping memories, called Associative Mapping Elements(AME) and Multiple-Digit Overlapping AME(MDO-AME), are presented for learning of nonlinear functions including kinematics and dynamics of robot manipulators. The proposed associative mapping memories consist of associative mapping rules(AMR) and weight update rules(WUR) which guarantee generalization and specialization of input-output relationship of learned nonlinear functions. Two simulation results, one for supervised learning and the other for unsupervised learning, are given to demonstrate the effectiveness of the proposed associative mapping memories.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.497-502
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• 1992

In this paper, a new design technique called Task Based Design (TBD) is proposed to design an optimal robot manipulator for a given task. Optimal design of a manipulator is difficult because it involves implicit and highly nonlinear functions of many design variables for a complex task. TBD designs an optimal manipulator which performs a given task best, by using a framework called Progressive Design which decomposes the complexity of the task into three steps: kinematic design, planning and kinematic control. An example of TBD is presented to demonstrate the efficiency and effectiveness of our framework.