• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.337-341
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• 1995

This paper presents a robust control scheme using a multilayer network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network acts as a compensator of the conventional sliding mode controller to maintain the control performance when the initial assumptions of uncertainty bounds are not valid. By the computer simulation results, the proposed control scheme dose not effectively compensate large uncertainties, but also reduces the steady stare error of the conventional sliding mode controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1046-1051
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• 1991

For the conveyor tracking application of a robot manipulator, a new control scheme is presented. The presented scheme is divided into two stages : the upper one is the motion planning stage and the lower one is the motion control stage. In the upper stage, the nominal trajectory which tracks the part moving in a constant velocity, is planned considering the robot arm dynamics. On the other hand, in the lower level, the perturbed trajectory is generated to track the variation in the velocity of conveyor belt via sensory feedback and the perturbed arm dynamics. In both stages, the conveyor tracking problem is formulated as an optimal tracking problem, and the torque constraints of a robot manipulator are taken into account. Simulation results are then presented and discussed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.299-301
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• 1994

Visual feedback has traditionally been used in robot manipulator control to a limited extent. However in varying environment, visual data is needed to control the manipulator to complete the desired task. In this paper we present a method of manipulator control scheme called image-based visual servo. In this scheme we use image data as feedback to control robot manipulator. And we also show the experimental results with an industrial robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2033-2038
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• 2003

This paper describes an integrated navigation strategy for the autonomous service robot PSR. The PSR is under development at the KIST for service tasks in indoor public environments. The PSR is a multi-functional mobile-manipulator typed agent, which works in daily life. Major advantages of proposed navigation are as follows: 1) Structured control architecture for a systematic integration of various software modules. A Petri net based configuration design enables stable control flow of a robot. 2) A range sensor based generalized scheme of navigation. Any range sensor can be selectively applied using the proposed navigation scheme. 3) No need for modification of environments. (No use of artificial landmarks.) 4) Hybrid approaches combining reactive behavior as well as deliberative planner, and local grid maps as well as global topological maps. A presented experimental result shows that the proposed navigation scheme is useful for mobile service robot in practical applications.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.570-573
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• 2000

A control law for a SCARA robot manipulator is designed using recursive torque methods. This scheme uses previous torques and error dynamics to generate torque controls at the present time and adopts relatively simple numerical and control algorithms that can be easily realizable. In order to evaluate the performance and robustness of the suggested control system, the 2-link SCARA robot manipulator is practically implemented using a dSPACE interface. It is found that the recursive controller has a good tracking performance in spite of the presence of payload disturbances.

• 제어로봇시스템학회논문지
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• 제12권12호
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• pp.1220-1230
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• 2006

In this paper, we propose a flew technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.113-118
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• 1999

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 n 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.

• 한국산업융합학회 논문집
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• 제23권2_1호
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• pp.149-161
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• 2020

We describe a new approach to implement of trajectory control and track record of articulated manipulator based on monitoring simulator for smart factory. The learning control algorithm was applied in implementation real-time control to provide enhanced motion control performance for robotic manipulators. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, or values of manipulator parameters and payload. Performance of the proposed controller is illustrated by simulation and experimental results for robot manipulator consisting of six joints at the joint space and Cartesian space.by monitoring simulator.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.63-64
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.490-493
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• 1996

This paper presents a control scheme for the motion of a 2 DOF robot manipulator. Robot manipulators are multivariable nonlinear systems. Fuzzy logic is avaliable human-like control without complex mathematical operation and is suitable to nonlinear system control. In this paper, Implementation of fuzzy logic control of robotic manipulators shows. Algorithm has been performed with simulation packages MATRIXx and SystemBuild.