• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.470-473
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• 1996

This paper presents an iterative learning control scheme for industrial manipulators. Based upon the frequency-domain analysis, the input update law of the learning controller is given together with a sufficient condition for the convergence of the iterative process in the frequency domain. The proposed learning control scheme is structurally simple and computationally efficient since it is independent joint control depending only on locally measured variables and it does not involve the computation of complicated nonlinear manipulator dynamics. Moreover, it is capable of canceling the unmodeled dynamics of the manipulator without even the parametric model. Several important aspects of the learning scheme inherent in the frequency-domain design are discussed and the control performance is demonstrated through computer simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.472-477
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• 1996

This paper presents a new approachtothe 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 adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and 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 simulation and experimental results for a SCARA robot.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.12
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• pp.983-994
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• 1989

This paper presents a new variable structure model following control algorithm for control of manipulators. The reference model is a simple double integrators and the acceleration input for the robot manipulator consists of a proportional and derivative controller for the purpose of trajectory tracking. The control algorithm is derived by using Lyapunov stability theory instead of S.S < O, as is usual in the current VSS controller design. This proposed control algorithm does not require good knowledge of the parameter in the inertia matrix and is easily extendable to robot manipulators with a higher number of links. Also, the new algorithm is computationally fast because of not requiring the matrix inversion. The computer simulation was carried out to evaluate the performance of the proposed VSMFC.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.422-432
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• 1992

Previous investigations of redundant manipulators have often focussed on local optimization for redundancy resolution by using the Jacobian pseudoinverse to solve the instantaneous relationship between the joint and end-effector velocities. This paper establishes some new goals for redundancy resolution at position level by using configuration control approach which has been recently developed. Minimum gravity loading, joint limit avoidance, minimum sensitivity, maximum stiffness and minimum impulse are introduced as redundancy resolution goals. These new goals for redundancy resolution allow more efficient utilizations of the redundant joints based on the desired task requirements. Simple computer simulation examples are given for illustration.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.394-396
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• 1992

This note is concerned with the point to point control of manipulators having elastic joints. We present a PD control algorithm which is adaptive with respect to the gravity and elastic parameters of robot manipulators. While the conventional control law is used, a new adaptive law is used to improve the performance. The proposed controller is shown to be stable. It is Shown that steady-state position error converges to zero through some simulations concerning the manipulator with three revolute elastic joints.

• ICROS
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• v.1 no.1
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• pp.16-16
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• 1995

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.16-20
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• 1999

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.385-392
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• 1993

This paper presents a new stable composite control law for the flexible joint robot manipulators, which incorporate an additional stabilizing control law with the sliding property. The singularly perturbated models in this paper include inertia moments which are functions or the deformations of actuators as well as link positions. The values of renewedly defined fast controller variables are computer from the corrected reduced-order model without additional computational loads. Proposed schemes are compared with the conventional one. The simulations for 2 DOF flexible joint manipulator show that the proposed schemes are more stable than the conventional scheme, and especially effective for the manipulator with high joint-flexibilities.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.255-260
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• 2001

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 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. 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

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 bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic 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 SCAEA robot.