• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.128-133
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• 2001

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

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.980-984
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• 2001

When robot manipulatros as mathematically modeled. uncetainties may not be avoided. The uncertain factors come from imperfect knowledge of system parameters, payload change. friction, external disturbance and etc. In this work, we proposed a class of robust hybrid control of manipulatosrs. We propose a class of expanded robust hybrid control with the separated bound function and the simulation results are provided to show the effectiveness of the algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.454-457
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• 2002

This paper presents a new motion control for singularity avoidance in 6 DOF articulated robot manipulators, based on a speed limiting algorithm for joint positions and velocities. For a given task, the robot is controlled so that the joints move with acceptable velocities and positions within the reachable range of each joint by considering the velocity limit. The proposed method was verified using MATLAB-based simulations.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.211-218
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• 1999

The traditional robot manipulators are actuated by continuous range of motion actuators such as motors or hydraulic cylinders. However, there are many applications of mechanisms and robotic manipulators where only a finite number of locations need to be reached, and the robot’s trajectory is not important as long as it is bounded. Binary manipulator uses actuators which have only two stable states. As a result, binary manipulators have a finite number of states. The number of states of a binary manipulator grows exponentially with the number of actuators. This kind of robot manipulator has some advantage compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. And this kind of robot manipulator has a fault tolerant mechanism because of kinematic redundancy. In this paper, we solve the inverse kinematic problem of a binary parallel robot manipulator using neural network and test the validity of this structure using some arbitrary points m the workspace of the robot manipulator. As a result, we can show that the neural network can find the nearest feasible points and corresponding binary states of the joints of the robot manipulator

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.68-75
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• 2003

This paper presents an effective trajectory planning algorithm for industrial robot manipulators. Given the end-effector trajectory in Cartesian space, together with the relevant constraints and task specifications, the proposed method is capable of planning the optimum end-effector trajectory. The proposed trajectory planning algorithm considers the joint acceleration limit, end-effector velocity limits, and trajectory allowance. A feedforward compensator is also incorporated in the proposed algorithm to counteract the delay in joint dynamics. The algorithm is carefully designed so that it can be directly adopted with the existing industrial manipulators. The proposed algorithm can be easily programmed for various tasks given the specifications and constraints. A three-dimensional test trajectory was planned with the proposed algorithm and tested with the Performer MK3s industrial manipulator. The results verified effective manipulator performance within the constraints.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1012-1016
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• 1991

An effective visual servo control system for robotic manipulators based on neural networks is proposed. For this control system, firstly, one neural network is used to learn the mapping relationship between the robot's joint space and the video image space. However, in the proposed control scheme, this network is not used in itself, but its first and second derivatives are used to generate servo commands for the robot. Secondly, an adaptive Adaline network is used to identify the dynamics of the robot and also to generate the proper torque commands. Computer simulation has been performed indicating its superior performance. As far as the authors know, this is the first time attempt of the use of neural networks for a visual servo control of robots that compensates for their changing dynamics.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.89-96
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• 2002

A new chattering free PD-sliding mode hybrid control scheme is proposed for robot manipulators. This hybrid controller is composed of a PD controller and a semi-continuous sliding mode controller. It has a good robust performance in reaching mode which does not possess invariance property of sliding mode, and has chattering free characteristics in sliding mode. Thus, the PD-sliding mode hybrid controller has a good robust performance in the whole region. It is shown that the proposed control has a good transient response and trajectory tracking performance for a 2-link SCARA robot manipulator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1601-1609
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• 1988

In the control of the robotic manipulators, the variable structure control method for the set point Regualation has an advantage of the insensitivity about parameter variations and disturbances. When the robotic manipulatores are controlled by a point-to-point scheme, no path constraint is considered. Thus, the variable structure control method will be effectively applied only if the trajectory of the robot hand is estimated precisely. In this paper, the joint trajectories in the joint space and the hand trajectory in the cartesian space are calculated by the variable structure control method, and an algorithm is suggested to elaborate the deviation error of the robot hand from a straight line path. The result of this study will become a base of the effective path planning about robotic manipulators with the variable structure control concept.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.753-763
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• 2015

This paper proposes a decentralized robust adaptive neural network control scheme using multiple radial basis function neural networks for electrically driven robot manipulators with bounded input voltages in the presence of uncertainties. The proposed controller considers both robot link dynamics and actuator dynamics. Practically, the controller gain coefficients applied at each joint may be nonlinear time-varying and the input voltage at each joint is saturated. The proposed robot controller overcomes the various uncertainties and the input voltage saturation problem. The proposed controller does not require any robot and actuator parameters. The adaptation laws of the proposed controller are derived by using the Lyapunov stability analysis and the stability of the closed-loop control system is guaranteed. The validity and robustness of the proposed control scheme are verified through simulation results.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.638-647
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• 1996

Robot manipulators for harvesting fruits must be controlled to track the desired path of end-effector to avoid obstacles under the consideration of collision free area and safety path. This paper presents a robot path control algorithm to secure a collision free area with the recognition of work environments. The flexible space, which does not damage fruits or branches of tree due to their flexibility and physical properties , extends the workspace. Now the task is to control robot path in the extended workspace with the consideration of collision avoidance and velocity limitation at the time of collision concurrently. The feasibility and effectiveness of the new algorithm for redundant manipulators were tested through simulations of a redundant manipulator for different joint velocities.