• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1160-1166
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• 2015

This paper proposes a decentralized robust adaptive control scheme for robot manipulators with input torque saturation in the presence of uncertainties. The control system should consider the practical problems that the controller gain coefficients of each joint may be nonlinear time-varying and the input torques applied at each joint are saturated. The proposed robot controller overcomes the various uncertainties and the input saturation problem. The proposed controller is comparatively simple and has no robot model parameters. The proposed controller is adjusted by the adaptation laws and the stability of the control system is guaranteed by the Lyapunov function analysis. Simulation results show the validity and robustness of the proposed control scheme.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.104-109
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• 1997

A robust controller design to corrdinate a robot manipulator under unknown system parameters and bounded disturbance inputs is presented in this paper. Generally, robust controllers require high input torque so that they may face input saturation in actual application due to the power limitation of the actuator. To solve this problem, an improved robust controller with saturated input torque using a fuzzy logic control is proposed. Numerical examples are shown to validate the proposed controller using two degree-of-freedom planar arm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1209-1217
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• 1997

This paper proposes the modeling of the dynamics of two cooperating robot manipulators performing the assembly job such as peg-in-hole while coordinating the payload along the desired path. The mass and moment of inertia of the manipulators and the payload are assumed to be unknown. To control the uncertain system, a robust control algorithm based on the computed torque control is proposed. Usually, the robust controller requires high input torques such that it may face input saturation in actual application. In this reason, the robust control algorithm includes fuzzy logic such that the magnitude of the input torque of the manipulators is controlled not to go over the hardware saturation while keeping path tracking errors bounded. A numerical example using dual three degree-of-freedom manipulators is shown.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.108-115
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• 1997

This paper presents a robust controller design for uncertain nonlinear systems with input saturation. In actual application, the robust controller may require a high input torque so that it faces input saturation due to power limitation of the system. The satruation problem may cause instability of the system. To improve this problem, a robust controller using a fuzzy logic control is proposed. The proposed controller keeps state errors bounded. To validate the proposed controller, an invert pendulum and its control system is set up. The experimental result shows bounded angular position errors under saturated input torques.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.138-144
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• 2000

Robot manipulators, which are nonlinear structures and have uncertain system parameters, have complex in dynamics when are operated in unknown environment. To compensate for estimate errors of the uncertain system parameters and to accomplish the desired trajectory tracking, nonlinear robust controllers are appropriate. However, when estimation errors or tracking errors are large, they require large input torques, which may not be satisfied due to torque limits of actuators. As a result, their stability can not be guaranteed. In this paper, a new robust control scheme is presented to solve stability problem and to achieve fast trajectory tracking in the presence of torque limits. By using fuzzy logic, new desired trajectories which can be reduced are generated based on the initial desired trajectory, and torques of the robust controller are regulated to not exceed torque limits. Numerical examples are shown to validate the proposed controller using an uncertain two degree-of-freedom underwater robot manipulator.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.697-702
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• 2004

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation, is studied from an input-output feedback linearization with adaptive algorithm. is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. In order to achieve the speed regulation with the consideration of improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. Simulation results are provided for illustration.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.256-262
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• 1998

The torque of SRM depends on phase current and the derivative of inductance. But the inductance of SRM is nonlinearly changed according to rotor position angle and phase current because of saturation in magnetic circuit, and it is difficult to control the desired torque. This paper proposes inductance modeling method using ANN(Artificial Neural Network) that is used to simulate the inductance which is nonlinearly varied with rotor position and current. The torque ripple is analyzed and input voltage and current condition to reduce torque ripple is simulated by inductance model.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.325-328
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• 2002

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation is studied from an input-output feedback linearization with adaptive algorithm. The $\pi$-model of induction motor is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. Simulation results are provided for illustration.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.161-164
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• 1996

The authors have recently proposed a new method for identifying Volterra kernels of nonlinear control systems by use of M-sequence and correlation technique. A specially chosen M-sequence is added to the nonlinear system to be identified, and the crosscorrelation function between the input and output is calculated. Then every crosssection of Volterra kernels up to 3rd order appears at a specified delay time point in the crosscorrelation. This method is applied to a saturation-type nonlinear feedback control system of mechanical-electrical servo system having torque saturation nonlinearity. Simulation experiments show that we can obtain Volterra kernels of saturation-type nonlinear system, and a good agreement is observed between the observed output and the calculated one from the measured Volterra kernels.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.6
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• pp.506-513
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• 2001

The torque of an SRM depends on the phase current and derivative of inductance. But an SRM is difficult to control the desired torques because of saturation in magnetic circuit An SRM is controlled by parameters of input voltage, and switch on , off angle The switch on off angles of an SRM regulate the magnitude and shape of current waveform and decide the magnitude and shape of torque This paper proposes an the optimization control scheme by adjusting both the switch on an switch off angle . The switch off angles are decided by reference of efficiency using simulation and experiments. The switch on angles are decided by load torque , And the dwell angles are controlled for torque control and speed control using GA-neural network which is used to simulated the reasonable switching angle.