• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2088-2100
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• 1994

Considerable attention has been given to controller designs that utilize the variable structure system theory in order to achieve robust tracking performance of robotic manipulators subjected to parameter variations and extraneous disturbances. However, the theory has not had wide spread acceptance in practical control engineering community due mainly to the worry of chattering which is inherently ever-existing in the variable structure system. This paper presents a novel type of fuzzy-sliding mode controller to alleviate the chattering problem. A sliding mode controller for robust robot control is firstly synthesized with an assumption that the imposed system uncertainties satisfy matching conditions so that certain deterministic performances can parameters and control rules are obtained from a relation between predetermined sliding surfaces and representative points in the error state space. A two degree-of-freedom robotic manipulator subjected to a variable payload and a torque disturbance is considered in order to demonstrate superior tracking performance accrued from the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1581-1584
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• 1997

This paper poropsed an efficient optimization technuque to resolve redundancy and a trajectory planning for a high precision control using proposed optimization technique. The proposed techniqus is the joint disturbance torque optimizatioin considering redundancy in the joing servo control. Joint disturbance torque is not unknown it is described dynamic equation ignored friction and viscosity. The proposed technique is used the dynamic equatiion included the joint disturbance torque characteristics. Numerical example of 3 joint planar redundant robot manipulator is simulated. In the 2-norm minimization of joint disturbance torque we compared pseudoinverse local optimization with proposed technique, and the results showed better the proposed technique. So the proposed technique can be highly precision controlled redundant robot manipulators in the joint servo control.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1047-1052
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• 2008

In this paper, we design an image-based robust controller to compensate uncertainties with image Jacobian and robot dynamics due to uncertain depth measurement and load variations. The proposed controller with eye-in-hand structure has separate terms to compensate each of uncertainties. The ultimate boundedness of the closed-loop system is proved by the Lyapunov approach. The performance of the proposed control system is demonstrated by simulation and experimental results a 5-link robot manipulator with two degree of freedom.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.156-160
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• 1993

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an inproved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing force coming from the difference between th actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.886-888
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• 1995

Models of industrial robot manipulators are characterized by highly nonlinear equation with coupling between the variables of motion. In this paper, a case study that illustrates the use or nonlinear state feedback to decouple the control of a two axis SCARA type robot manipulator is presented. This method is based on a suitable partition about the dynamic equation of industrial robots. The performance of this method is showed by the computer simulation.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2588-2590
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• 2003

The part of manipulators is normally studied with regularized environmental conditions. however, it is the most difficult that the part of AMR must be studied with uncertainty in the environmental conditions. The part of AMR has skelton, sensor fusion, path planning etc. This paper is the research of the local pass planning that gathers information about external environment using neural network from each sensors and designs the algorithm which can determine which correct direction the robot can find. As the result of the research, AMR has been able to drive similarly as if the expert does and has been able to observe it acting without any control.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1217-1222
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• 2004

This paper describes the development of tele-robotic interface for the hot-line maintenance robot system. One of main issues in designing human-robot interface for the hot-line maintenance robot system is to plan the control procedure for each part of the robotic system. Another issue is that the actual degree of freedom (DOF) in the hot-line maintenance robot system is much greater than that of available control devices such as joysticks and gloves in the remote-cabin. For this purpose, a virtual simulator, which includes the virtual hot-line maintenance robot system and the environment, is developed in the 3D environment using CAD data. It is assumed that the control operation is done in the remote cabin and the overall work process is observed using the main-camera with 2 DOFs. For the input device, two joysticks, one pedal, two data gloves, and a Head Mounted Display (HMD) with tracker sensor were used. The interface is developed for each control mode. Designed human-interface system is operated using high-level control commands which are intuitive and easy to understand without any special training.

• Journal of Drive and Control
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• v.17 no.4
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• pp.31-37
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• 2020

We are concerned with the dual-arm manipulation for disaster-responding special-purpose machinery. This paper presents a control strategy for performing complex work in an irregular environment, the control algorithm, the hydraulic circuit, and the master devices. The occurrence of collapse accidents at disaster sites such as natural disasters and building collapses is increasing, which is emerging as a social problem. In particular, for the initial response, various tasks must be performed in an irregular environment. The Marionette algorithm for intuitive control of 'as if the operator's arm is moving' was presented as a control strategy for dual-arm manipulators with attachments and the prototype. Next, the hydraulic circuit, control system, and wearable-type master device presented to implement the Marionette algorithm were explained and verified through an experiment in which rebar-cutting, drum-lifting, and lifting a bottle with one arm and pouring the water into the bucket with the other arm were tested.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.679-684
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• 1989

In this paper, we describe the PTP notion of robot manipulators by neural networks. The PTP motion requires the inverse kinematic redline and the joint trajectory generation algorithm. We use the multi-layered Perceptron neural networks and the Error Back Propagation(EBP) learning rule for inverse kinematic problems. Varying the number of hidden layers and the neurons of each hidden layer, we investigate the performance of the neural networks. Increasing the number of learning sweeps, we also discuss the performance of the neural networks. We propose a method for solving the inverse kinematic problems by adding the error compensation neural networks(ECNN). And, we implement the neural networks proposed by Grossberg et al. for automatic trajectory generation and discuss the problems in detail. Applying the neural networks to the current trajectory generation problems, we can refute the computation time for trajectory generation.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1718-1719
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• 2007

In this paper, a fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for manipulators with uncertainties. Especially the system uncertainties is approximated using fuzzy rule adaptation technique. The proposed controller is composed of the equivalent control that includes the approximation of the system uncertainties and the hitting control that is used to constrain the states of the system to maintain on the sliding surfaces and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller