• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.9
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• pp.655-662
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• 1988

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a deired trajectory in spite of the presence of nonlinearies and parameter uncertainties in robot dynamic models. In this paper, an adaptive control scheme for a robot manipulator is proposed to design the self-tuning controller which controls the extended linearized perturbaton model via the pole placement, and this control. The feasibility of the controller is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.150-155
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using digital signal processors for robot manipulators. TMS3200C50 is used in implementing real-time adaptive control algorithms provide advanced performance for robot manipulator. In this paper an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm and controller parameters are detemined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.754-758
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS320C50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator, In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.32-35
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• 1987

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonlinearties and parameter uncertainties in robot dynamic models. In this paper, an adaptive control scheme for a robot manipulator is proposed to design the self-tuning controller which combines the pole placement with the extended linearized perturbation model. And this control scheme has two components: a feadforward control and a feedback compensation control. Based on this, the controller is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.228-234
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• 2005

In this paper, we proposed a self tuning adaptive fuzzy sliding control algorithms using gadient descent method to reduce chattering phenomenon which is viewed in variable control system. In design of FLC, fuzzy control rules are obtained from expert's experience and intuition and it is very difficult to obtain them. We proposed an adaptive algorithm which is automatically updated by consequence part parameter of control rules in order to reduce chattering phenomenon and simultaneously to satisfy the sliding mode condition. The proposed algorithm has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.39.2-39
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• 2002

This paper presents adaptive add-on control algorithms for theconventional mode of operation of MEMS z-axis gyroscopes. This scheme is realized by adding an outer loop to a conventional force-balancing scheme that includes a parameter estimation algorithm. The parameter adaptation algorithm estimates the angular rate, identifies and compensates the quadrature error, and may permit on-line automatic mode tuning. The convergence and resolution analysis show that the proposed adaptive add-on control scheme prevents the angular rate estimate from being contaminated by the quadrature error, while keeping ideal resolution performance of a conventional force-balancing scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.273-273
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• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.