• 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 of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.755-760
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• 2013

The dynamics of the winder roller of a roll-to-roll printing system for printed electronics is a time-varying system because of the variation of the winder roller radius owing to rewinding or unwinding of the web. Therefore, an adaptive control method considering the time-variant characteristics is required for precise tension control. In this study, the variable PID gain method is applied to the actual roll-to-roll system and verified by experiments for unwinder tension control. The required value of the winder roller radius for the application of the variable PID gain is estimated from the measurement of the winder tension and winder motor torque. The simulation results as well as experimental results show that the fixed PID gain control cannot stabilize the tension of the winder roller with varying winder roller radius. On the other hand, the variable PID gain method can control the tension of the winder roller regardless of the winder roller radius.

• Journal of Power System Engineering
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• v.19 no.4
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• pp.89-96
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• 2015

This paper investigates some strategies to overcome the chattering problem of the conventional sliding mode observer (SMO) and to improve the rotor position estimation performance for full range sensorless control of a PMSM. An adaptive observer gain based on the Lyapunov's stability criterion and a cascade low pass filter with advanced phase delay compensation were proposed to reduce the chattering problem and to strengthen the filtering capability of the SMO. Several cases studies through experiments were carried out to confirm conventional SMO's problems and effectiveness of the proposed strategies. The experimental results show that the proposed method gives precise estimation on speed and rotor position when the motor rotates on 2% of its rated speed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.12
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• pp.1170-1176
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• 2010

This study addresses adaptive control of UAVs(Unmanned Aerial Vehicles) pitch-axis maneuver. The MRAC(Model Referenced Adaptive Control) approach is employed to accommodate uncertainties which are introduced by feedback linearization of pitch attitude control by elevator input. The model uncertainty is handled by adaptation laws which update model parameters while the UAV is under control by the feedback control law. Steady-state pitch attitude achieved by the stabilizing control law is derived to provide insight on the closed-loop behavior of the controlled system. The proposed idea is free of linearization, gain-scheduling procedures, so that one can design high maneuverability of UAVs for pitching motion in the presence of significant model uncertainty.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.307-312
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• 2021

This paper proposes an adaptive time-delayed control approach with the integral sliding-mode surface for the fast convergence rate of robot manipulators. Adaptive switching gain aims to guarantee the system stability in such a way as to suppress time-delayed estimation error in the proposed control approach. Moreover, it makes an effort to increase the convergence ability in reaching the phase. An integral sliding-mode surface is employed to achieve a fast convergence rate in the sliding phase. The stability of the proposed one is proved to be asymptotically stable in the Lyapunov stability. The efficiency of the proposed control approach is illustrated with a tutorial example in robot manipulator, which is compared to that of the existing control approach.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.103-107
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• 2009

PI controller is widely used as voltage control system of generator. However when a generator system has various characters of continuance, a new PI parameter decision for accurate control is a hard task as method of solving this problem, in this paper, the method to generator voltage control using Neural Network self adaptive control is presented. A property continuous feedback control gain of voltage control system is decided by a rule of delta learning. The function of proposed control method is verified by voltage control experiment results of DC generator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1167-1177
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• 1989

In this paper, a generalized adaptive law is proposed which uses a rational function type operator for parameter adjustment. To satisfy the passivity condition of the adaptation block, we introduce a constant feedback gain into the adaptation block. This adaptation scheme is applied to the model reference adaptive control of a continuous-time, linear time-invariant, minimum-phase system whose relative degree is 1. We prove the asymptotic stability of the output error of this adaptive system by hyperstability method. It is shown that by digital computer simulations this law can give a better output error transient response in some cases than the conventional gradient adaptive law. And the output error responses for the several types of the proposed adaptation law are examined in the presence of a kind of unmodeled dynamics.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.998-1003
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• 2013

This study proposes an adaptive control algorithm for lateral motion of a UGV (Unmanned Ground Vehicle) using an NN (Neural Networks). The lateral motion of the UGV can be corrupted with various uncertainties such as side slip. In order to compensate the performance degradation of the UGV under various uncertainties, an NN-based adaptive control is designed by utilizing a virtual control concept. Since both the drift and input gain terms are uncertain, the proposed method adapts the whole terms related to the difference between the nominal and real systems. To avoid a singularity problem with the adaptive control, the affine property of the UGV dynamic model is utilized and the overall closed-loop stability is analyzed rigorously. Finally, numerical simulations using Carsim are performed to validate the effectiveness of the proposed scheme.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1295-1298
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• 2003

The steam generator level in a PWR is very difficult to control particularly at low power. And the constant control gain and time value are not adaptive in steam generator level controller. In normal operation constant control gain and time value have no problem. But there is problem at low power. So variable control gains based on the temperature are required. The best control gain is decided by the experienced knowledge. A fuzzy gain tuner is used for the gain tuning. In the design of fuzzy gain-tuner processing, the experienced knowledge is employed for making fuzzy rules.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.280-285
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• 2007

This paper presents a robustly adaptive flux observer for speed-sensorless induction motor control. The proposed approach employs additional robustifying signals to cope with the parametric uncertainties instead of designing an estimator, which has been normally used in power electronic drives. For that, the sliding-mode like adaptive controls are designed and their gain parameters are determined so that the observer dynamics are stable in the sense of Lyapunov, and furthermore they can guarantee the robustness against parametric uncertainties in induction motor systems. Estimated rotor speed is to be used to generate feedback control signal for the speed sensorless vector control system. To show the validity and efficiency of the proposed system, simulation results are presented.