• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.687-693
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• 1989

A robust deterministic control for a class of singularly perturbed uncertain systems, where uncertainties are characterized deterministically rather than stochastically, is developed based mainly on information available on an uncertain reduced-order system. The deterministic control scheme is applied to the motion control of a n degree of freedom robotic manipulator. The parasitic actuator and sensor dynamics of the manipulator are explicitly considered in the stability analysis of the deterministic controller using a singular perturbation model. Simulation and experimental studies for a two degree of freedom, direct drive SCARA manipulator are conducted to evaluate the effectiveness of the derived control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.32-36
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• 1988

Generally, for nonlinear control of robotic system, the method of computed torque or inverse dynamics is frequently used. In this case, exact knowledge of the system parameters is required, however. This paper addresses the problem of nonlinear control when the parameter of system is varied. The approach is based upon decoupled model following. As an example, control of a three degree of freedom manipulator arm under mass variation is simulated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.455-458
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• 2003

An optimal control approach to robust control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method to find the matrix is shown. Simulations arc made for a weight-lifting operation of a two-link manipulator and the robust control performance of robotic systems by the proposed algorithm is remarkable.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.298-303
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• 1986

A robust and efficient dynamic control algorithm for the position control of robotic manipulators is proposed. This algorithm consists of an open loop control and a closed loop control. The former may have a larger sampling time than the latter. The robustness and efficiency of this algorithm is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.348-348
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• 2000

In this paper, we present a fuzzy moving sliding mode control for two-degrree-of-freedom robotic manipulator. 17he sliding surface parameters are designed by fuzzy inference. The proposed sliding mode control makes the error always remain on the surface from beginning and therefore, the system is insensitive to system uncertaintics and external disturbances. Simulation results show the effectiveness of proposed scheme.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.176-182
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• 2003

An optimal control approach to robust control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method to find the matrix is shown. Simulations are made for a weight-lifting operation of a two-link manipulator and the robust control performance of robotic systems by the proposed algorithm is remarkable.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.165-173
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• 1995

In order to eliminate position errors existing at the steady state in the motion control of robotic maniprlators, a new fuzzy control algorithm is proposed using three variables, position error, velocity error and integral of position errors as input variables of the fuzzy controller, This controller is applied to the tracking control of robotic manipulators in Cartesian space. Three dimensional look-up table is used to reduce the computational time in rel-time control. Simulation and experimental studies are conducted to evaluate the control performance for the two axis direct drive SCARA robot system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.96-101
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• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.162-168
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• 1998

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. This paper develops algorithms for kinematics and workspace analysis of a binary manipulator.