• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.210-213
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• 1999

In this paper, we propose a new neural network for the control of a robot manipulator The proposed neural network structure is that all of network outputs feed bark into hidden units and output units from feedback units The feedback units are only to memorize the previous activations of the hidden units and output units and can be considered to function as one-step time delays. The proposed neural network works standard back-propagation Loaming algorithm. The simulation and experiment results showed the effectiveness of using the modified neural network structure in the control of the robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.293-298
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• 1993

In this paper, methods for computing the time-optimal motion of a robotic manipulator are presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem can be reduced to a search for the time-optimal path in the n-dimensional position space. These paths are further optimized with a local path optimization to yield a global optimal solution. Time-optimal motion of a robot with an articulated arm is presented as an example.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.139-149
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• 2015

In this paper, we describe a new approach to perform real-time implementation of an robust controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs 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 direct Lyapunov 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 robot manipulator consisting of dual arm with eight degrees of freedom at the joint space and cartesian space.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.11
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• pp.2011-2020
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• 1992

This paper discusses about real time control applying sliding mode to robot manipulators whose nonlinear terms, which are inertia term, Corilis term and centrifugal force mterm, are regarded as disturbances. We could simplify the dynamic equations of a manipulator and servo system, which are composed of linear elements and nonlinear elements, by assuming that non-linear terms are external disturbance. By simplifying that equation, we could easily obtain a control input which satisfy sliding mode. We proposed a new control input algorithm to decrease chattering in the application of sliding mode control of manipulator whose nonlinear elements are regarded as disturbances. We could take impulse response of linear elements of dynamic equations of a robot manipulator and servo system by Signal Compression Method. So then, we could obtain the unknown parametes of its linear lements, which are used to obtain switching parameter satisfying sliding mode, by Signal Compression Method. In this experiments, we used DSP(Digital Signal Processor) controller to suppress chattering by obtaining a switching speed and to carry out real time control.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.94-104
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.32-39
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• 2008

This paper reports on a realtime OS based master-slave configuration robot control system for laparoscopic surgery robot which enables telesurgery and overcomes shortcomings with conventional laparoscopic surgery. Surgery robot system requires control system that can process large volume information such as medical image data and video signal from endoscope in real-time manner, as well as precisely control the robot with high reliability. To meet the complex requirements, the use of high-level real-time OS (Operating System) in surgery robot controller is a must, which is as common as in many of modem robot controllers that adopt real-time OS as a base system software on which specific functional modules are implemened for more reliable and stable system. The control system consists of joint controllers, host controllers, and user interface units. The robot features a compact slave robot with 5 DOF (Degree-Of-Freedom) expanding the workspace of each tool and increasing the number of tools operating simultaneously. Each master, slave and Gill (Graphical User Interface) host runs a dedicated RTOS (Real-time OS), RTLinux-Pro (FSMLabs Inc., U.S.A.) on which functional modules such as motion control, communication, video signal integration and etc, are implemented, and all the hosts are in a gigabit Ethernet network for inter-host communication. Each master and slave controller set has a dedicated CAN (Controller Area Network) channel for control and monitoring signal communication with the joint controllers. Total 4 pairs of the master/slave manipulators as current are controlled by one host controller. The system showed satisfactory performance in both position control precision and master-slave motion synchronization in both bench test and animal experiment, and is now under further development for better safety and control fidelity for clinically applicable prototype.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.280-284
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• 1997

In this paper, Nonlinear VSS control based on bang-bang control concept is derived under the assumption that the control input is bounded. We try to derive control algorithm which has almost same performance as the time optimal control. We focus this control scheme on the real implementation of DC motor position controller of flexible link, i.e. we obtain the switching curves from the real data of DC motor system operating under the full maximum and minimum applied voltages. State space is separated into several regions and we set different switching surfaces in each region to reduce chattering problem. The efficiency of the proposed controller is compared with PID controller and it is shown that the controller converges fast than PID controller without chattering. The hybrid controller scheme is also proposed not only to control the position of hub but also to reduce the vibration of end tip of flexible link.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.267-276
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• 1993

This paper discusses the neural network application in the study on the obstacle avoidance of robot manipulator during the trajectory planning. The collision problem of two robot manipulators which are simultaneously moving in the same workspace is investigated. Instead of the traditional modeling method, this paper processing based on the calculation of joint angle in the cartesian coordinate with constrained condition shows the possibility of real time control. The problem of the falling into the local minima is cleared by the adaptive weight factor control using the temperature adding method. Computer simulations are shown for the verification.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.417-420
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• 1987

For an increased level of productivity, it is important that the end-point of a robot manipulator moves from an initial location to final position in the minimum time subject to the available maximum actuator's torque (or force) at each joints. The main issue is to develop an algorithm to compute the actuators in real-time. In this paper, a digital state feedback control algorithm has bean developed to obtain the near-minimum-time trajectory for the end-effector of a robot manipulator. In this algorithm, the poles of the linearized closed loop system are judiciously placed in the Z-plane to permit minimum-time response without violating the constraints on the actuator torques. The validity of this algorithm have been established using numerical simulations. A three-link manipulator in chosen for this purpose and results are discussed for three different combinations of initial and final station.

• Journal of the Korean Institute of Navigation
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• v.21 no.3
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• pp.55-66
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• 1997

In this paper, applications of neural networks to vibration control of flexible single link robot manipulator are ocnsidered. The architecture of neural networks is a hidden layer, which is comprised of self-recurrent one. Tow neural networks are utilized in a control system ; one as an identifier is called neuro identifier and the othe ra s a controller is called neuro controller. The neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by dynamic error-backpropagation algorithm(DEA). To guarantee concegence and to get faster learning, an approach that uses adaptive learning rates is developed by introducing a Lyapunov function. When a flexible manipulator is ratated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlle dinsuch as way, that the motor is rotated by a specified angle. while simulataneously stabilizing vibration of the flexible manipulators so that it is arrested as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large body motions, as well as the flexural vibrations. Therefore, dynamic models for a flexible single link manipulator is derived, and LQR controller and nerual networks controller are composed. The effectiveness of the proposed nerual networks control system is confirmed by experiments.