• 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 the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.8
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• pp.42-47
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• 2006

In this paper, we propose a sliding mode control with the bound estimation for robot manipulators without requiring exact knowledge of the robot dynamics. For the bound estimation, the upper bound of the uncertain nonlinearities of robot dynamics is represented as a Fredholm integral equation of the first kind and we propose an adaptive scheme which is only dependent on the sliding surface function. Also, we prove the asymptotic stability for the robot systems using two important properties in the robot dynamics: skew-symmetry and positive-definiteness of robot parameters.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.162-170
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• 2003

In this paper, we propose a robust controller for trajectory control of n-link robot manipulators using feature based on visual feedback. In order to reduce tracking error of the robot manipulator due to parametric uncertainties, integral action is included in the dynamic control part of the inner control loop. The desired trajectory for tracking is generated from feature extraction by the camera mounted on the end effector. The stability of the robust state feedback control system is shown by the Lyapunov method. Simulation and experimental results on a 5-link robot manipulator with two degree of freedom show that the proposed method has good tracking performance.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.666-671
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• 1993

A new robust control law is proposed for uncertain rigid robots and two composite robust control laws for flexible-joint manipulators which contain uncertainties. The uncertainty, is nonlinear and (possibly fast) time-varying. Therefore, the uncertain factors such as imperfect modeling, function, payload change, and external disturbances are all addressed. Based only on the possible bound of the uncertainty, a robust controller is constructed for the rigid counterpart of the flexible-joint robot Some feedback control terms are then added to the robust control law to stabilize the elastic vibrations at the joints. To show that the proposed composite robust control laws are indeed applicable to flexible-joint robots, a singular perturbation approach and the stability study based on Lyapunov function are proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.117-122
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• 1994

In this paper, we discuss the modeling of flexible manipulators. In the modeling of flexible manipulators, there are two approaches: one is based on the distributed-parameter modeling and the other on the lumped-parameter modeling. The former has been applied to control and analysis of simple manipulator requiring precision, while the latter has been applied to multi-link spatial manipulator, because of the model's simplicity. We have already proposed the lumped-parameter modeling method for simple manipulator, and investigate that model of how much degree of precision we can get. The experiments and simulations are performed, comparing these results, the approximate performance of our modeling method is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.324-327
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• 1994

In this paper, a new design method of variable structure model following control system(VSMFCS) for robot manipulators is proposed. The proposed controller overcomed reaching phase problem by using function augmenting scheme to the sliding surface. Therefore, it can be guaranteed that the overall system always has a robust property against parameter variations and external disturbances. Furthermore, the proposed controller does not use the model state, .chi.$_{m}$, different from other previous works. Regardless of not using the model state, the model following error dynamics, virtual dynamics, is shown to be globally exponentially stable. The efficiency of the proposed method has been demonstrated by an example.e.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.76-81
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• 1994

A compliance control method of redundant manipulators is presented. This method is based on the new stiffness model, which allows us to modulate accurate joint stiffness of realizing the end effector stiffness to be varied with task requirements. Control model is developed and by implementing the proposed method in a three-dof(degree of freedom) planar redundant manipulator, its effectiveness is validated.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.89-94
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• 1994

This paper presents an impact control algorithm for reducing the potentially damaging effects by interation of redundant manipulators with their environments. In the. proposed control algorithm, the redundancy is resolved at the torque level by locally minimizing joint torque, subject to tire operational space dynamic formulation which maps tire joint torque set into the operational forces. For a given pre-impact velocity of the manipulator, the proposed approach is on generating joint space trajectories throughout the motion near the contact which instantaneously minimize the impulsive force which is a scalar function of manipulator's configurations. This is done by using the null space dynamics which does not affect the motion of an end-effector. The comparative evaluation of the proposed algorithm with a local torque optimization algorithm without reducing impact is performed by computer simulation. The simulation results illustrate the effectiveness of the algorithm in reducing both the effects of impact and large torque requirements.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.495-505
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• 2006

A class of robust control for flexible joint manipulators with nonlinearity mismatched uncertainty is designed based on Lyapunov approach. The uncertainties are unknown but their values are within certain prescribed sets. No statistic information of the uncertainties is imposed. The control which utilizes state transformation via virtual control is proposed. The resulting robust control guarantees practical stability for the transformed system and later the stability for the original system is proved. The designed robust control is implemented by experiments in a 2-link flexible joint manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in 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. 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. The TMS32OC31 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.