• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.206-212
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• 2000

This paper presents a hybrid actuator scheme to actively control the end-point position and vibration of a two-link flexible robot arm. Control scheme consists of four different actuators; two servo-motors at the hubs and two piezoceramics bonded to the surfaces of the flexible links. Two sliding hyperplanes are designed for two servo-motors which have time varying parameters to maintain control performance in any configuration. The surface gradients of the hyperplanes are determined by pole assignment technique to guarantee the stability on the hyperplanes themselves. During the motion, undesirable oscillations caused by the torques based on the rigid link dynamics are actively suppressed by applying feedback control voltages to the piezoceramic actuators. Consequently, desired tip motion is achieved. In order to demonstrate the effectiveness of the proposed methodology, experiments are performed for the regulating and tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.1
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• pp.37-43
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• 1996

This paper presents a new control scheme for decoupling the dynamics of two coordinating robot manipulators. A simple full-state feedback scheme with configuration dependent gains can be devised to decouple the system dynamics such that the dynamics of each arm and that of an object held by the two arms is independent of one another. A condition for stability is shown. The advantage of the proposed scheme is that the same control scheme can be applied both for the closed kinematic chain(object-grasping) case and open kinematic chain(no object-grasping) case.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.312-317
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• 1992

This paper proposes a new framework of an autonomous and distributed flexible manufacturing system - Multi Client Robot Groups(MCR) - and describes a stochastic learning scheme applied to managerial problems of the system. The MCR is composed of groups of manufacturing robots, named Client Robots (CRs), which are capable of both versatility and independence in their performances. The MCR is expected to have high performance because the MCR can perform concurrent and corporative processing. However, the system performance is determined by the organizations of the CR groups. Therefore the treatment of the managerial problems and organizations of the system are important problems. In this paper, it is assumed that CR groups being able to processing tasks are selected stochastically based on the strengths of the robot groups. The learning scheme adjusting the strength is introduced to organize the groups in the system and control the each performance of the groups according to the total system performance. Finally, some experimental results of the learning scheme are shown.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1269-1271
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• 1996

This paper presents a visual servoing combined by evolutionary algorithms and neural network for a robotic manipulators to control position and orientation of the end-effector. Using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we generate the control input to agree the target image, to realize the visual servoing. The validity and effectiveness of the proposed control scheme will be verified by computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.789-797
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• 2003

An implementation scheme and some improvements are proposed to adopt public-licensed operating system, Linux and de-facto world-wide network standard, TCP/IP into the field of behavior-based autonomous mobile robots. To demonstrate the needs of scheme and the improvement, an analysis is performed on a server/client communication problem with real time Linux previously proposed, and another analysis is also performed on interactions among TCP/IP communications and the performance of Linux system using them. Implementation of behavior-based control architecture on real time Linux is proposed firstly. Revised task-scheduling schemes are proposed that can enhance the performance of server/client communication among local tasks on a Linux platform. A new method of TCP/IP packet flow handling is proposed that prioritizes TCP/IP software interrupts with aperiodic server mechanism as well. To evaluate the implementation scheme and the proposed improvements, performance enhancements are shown through some simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.650-655
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• 2016

In this paper, a novel RLS-based DOB (Recursive Least Squares Disturbance Observer) scheme is proposed to improve the performance of DOB for nominal model identification. A nominal model can be generally assumed to be a second order system in the form of a proper transfer function of an ARMA (Autoregressive Moving Average) model. The RLS algorithm for the model identification is proposed in association with DOB. Experimental studies of the balancing control of a one-wheel robot are conducted to demonstrate the feasibility of the proposed method. The performances between the conventional DOB scheme and the proposed scheme are compared.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.999-1005
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• 1988

An iterative learning control scheme is presented with the aid of CMAC module. By enforcing the role of linear controller with the introduction of velocity feedback, it becomes possible to make the trajectory error equation stable. One advantage of this control scheme is that it does not require acceleration feedback. Computer simulation results shows a good performance of the scheme even in the case where the gravity is not compensated.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.568-577
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• 2000

In this paper for an object grasped by a robot hand to work in stiffness control domain we first investigate the number of fingers for successful stiffness modulation in the object operational space. Next we propose a new compliance control method for robot hands which consist of two steps. RIFDS(Resolved Inter-Finger Decoupling Solver) is to decompose the desired compliance characteristic specified in the op-erational space into the compliance characteristic in the fingertip space without inter-finger coupling and RIJDS(Resolved Inter-Joint Decoupling Solver) is to decompose the fingertip space without inter-finger coupling and RIJDS(Resolved inter-Joint Decoupling Solver) is to decompose the compliance characteristic in the finger-tip space into the compliance characteristic given in the joint space without inter-joint coupling. Based on the analysis results the finger structure should be biominetic in the sense that either kniematic redundancy or force redundancy are required to implement the proposed compliance control scheme, Five-bar fingered robot hands are used as an illustrative example to implement the proposed compliance control method. To show the effectiveness of the proposed compliance control method simulations are performed for two-fingered and three-fingered robot hands.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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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 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.5 no.2
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• pp.220-227
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• 1999

The position control accuracy of a robot arm is significantly deteriorated when a long slender arm robot is operated at a high speed. In this case, the robot arm needs to be modeled as a flexible structure, not a rigid one, and its control system needs to be designed with its elastic modes taken into account. In this paper, the vibration control scheme of a one-link flexible manipulator using adaptive input shaper in conjunction with PID controller is presented. The robot consists of a flexible arm manufactured with a thin aluminium plate, an AC servo motor with a harmonic drive for speed reduction, an optical encoder and an accelerometer. On-line identification of the vibration mode is done using the pruned decimation-in-time FFT algorithm to estimate the parameter of the input shaper. Experimental results of the flexible manipulator with a PID controller and input shaper are provided to show the effectiveness of the advocated controllers.