• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve 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 control 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 auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.1-7
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• 1998

Robots utilized in the field of welfare or agriculture should be light in weight and flexible in structure. A pneumatic actuator has properties such that it is more powerful compared with a motor of same weight, and that it is flexible, clean and unexplosive. In this paper we propose a new structure of the pneumatic actuator with two-degree-of-freedom. By using proposed pneumatic actuators, we can easily construct multi-degree-of-freedom pneumatic manipulators. Here we constructed a fourteen-degree-of-freedom pneumatic dual manipulator. The performance of the dual manipulators is confirmed through experiments for ball-handling with impedance control. In the experiments several control schemes, including the decentralized control and the simple adaptive control (SAC), were used. The results show that a flexibility of the pneumatic actuator is appropriate to accomplish the coordinative motion of the right and left arms of the robot.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.20-25
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• 1998

This paper proposes a new compliant contact control strategy for the robot manipulators accidentally interacting with an unknown environment. The main features of the proposed method are summarized as follows: First, each entry in the diagonal stiffness matrix corresponding to the task coordinate in Cartesian space is adaptively adjusted during con-tact along the corresponding axis based on the contact force with its environment. Second, it can be used for both unconstrained and constrained motions without any switching mechanism which often causes undesirable instability and/or vibrational motion of the end effector. Third, the adjusted stiffness gains are automatically recovered to initially specified stiffness gains when the task is changed from constrained motion to unconstrained motion. The simulation results show the effectiveness of the proposed method by employing a two-link direct drive manipulator interacting with an unknown environment.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.513-518
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• 1998

In this paper, a robust fault-tolerant control scheme for robot manipulators overcoming actuator failures is presented. The joint(or actuator) fault considered in this paper is the free-swinging joint failure and causes the loss of torque on a joint. The presented fault-tolerant control framework includes a normal control with normal(non-failed) operation, a fault detection and a fault-tolerant control to achieve task completion. For both no uncertainty case and uncertainty case, a stable normal con-troller and an on-line fault detection scheme are presented. After the detection and identification of joint failures, the robot manipulator becomes the underactuated robot system with failed actuators. A robust adaptive control scheme of robot manipulators with the detected failed-actuators using the brakes equipped at the failed(passive) joints is proposed in the presence of parametric uncertainty and external disturbances. To illustrate the feasibility and validity of the proposed fault-tolerant control scheme, simulation results for a three-link planar robot arm with a failed joint are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.519-524
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• 1998

This paper presents a robust control scheme of free-joint manipulators to overcome actuator failures and uncertain-ties in Cartesian space where tasks are planned. The control scheme has the adaptation law for the upper bound on the norm of uncertainties through the Lyapunov function approach. To solve the dynamic singularity problem in the controller, the singular and nonsingular regions are investigated based on a computer simulation. Then a singularity-free Cartesian trajectory planning is achieved in order to guarantee the availability of the control scheme. To illustrate the validity of the proposed control scheme, simulation results for a three-link planar robot arm with a free joint are shown.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.330-336
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• 2005

An intelligent control method is proposed for control of rigid robot manipulators which achieves exponential tracking of repetitive robot trajectory under uncertain operating conditions such as parameter uncertainty and unknown deterministic disturbance. In the learning controller, exponentially stable learning algorithms are combined with stabilizing computed error feedforward and feedback inputs. It is shown that all the error signals in the learning system are bounded and the repetitive robot motion converges to the desired one exponentially fast with guaranteed convergence rate. An engineering workstation based control system is built to verify the effectiveness of the proposed control scheme.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.993-1000
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• 2001

Configuration-dependent nonlinear coefficient matrices in the dynamic equation of robot manipulator impose computa- tional burden in real-time implementation of tracking control based on the inverse dynamics controller. However, parallel manipulators such as Stewart platform have relatively small workspace compared to serial manipulators. Based on the characteristics of small motion range. nonlinear coefficient matrices can be approxiamted to constant ones. The modeling errors caused by such approximation are compensated for by H-infinity controller that treats the modeling errors disturbance. The proposed inverse dynamics controller with approximate dynamics combined with H-infinity control shows good tracking performance even for fast tracking control in which computation of full inverse dynamics is not easy to implement.

• 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 Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.