• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.339-346
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• 2022

To operate in real environment, humanoid robots should be able to react to unknown disturbances. To deal with disturbances, various robust control algorithms have been developed for decades. But for collaborative works such as teleoperation system, a compliance control can be the better solution for disturbance reactions. In this paper, a center of mass (CoM) compliance control algorithm for humanoid robots is proposed. The proposed algorithm is based on the state observer and positive feedback of disturbance. With the state observer based on humanoid CoM control performance model, disturbance in each direction can be observed. The positive feedback of disturbances to the reference CoM trajectory enables compliant motion. The main contributions of this algorithm are achieving compliance independently in each axis and maintaining balance against external force. Through dynamic simulations, the performance of the proposed method was demonstrated. Under two types of disturbance conditions, humanoid robot DYROS-JET reacted with compliant motion via the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.62-68
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• 1998

In this paper, a speed controller considering the effects of parameter variations and external disturbance for induction motor driver is designed. An proportional plus integral(P1) fuzzy controller is designed to match desired speed tracking specification. Then a robust controller using Fuzzy Weight matrix are designed that in order to reduce the effect of parameter variations caused by external disturbance. The desired speed tracking control performance of the driver is preserved under wide operating range, and also good speed performance is confirmed by the computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.346-349
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• 1994

This paper is concerned with a motion control of a manipulator under parametric uncertainties and external disturbances. The parametric uncertainties are regarded as internally generated disturbances in the manipulator. Based on this idea, we formulate a model reference control problem with desired disturbance attenuation. The solution of this control problem not only reduces the worst-case effect on tracking error due to internal and external disturbances (combined disturbances) as much as possible, but also achieve optimal tracking when perturbations are absent. In order to solve the control problem which is formulated in this paper we reduce it to a constrained minmax cost control problem. A differential game theory is used to treat this constrained minmax cost control problem. The differential game theory leads to a sufficient condition for the global solvability of the model reference control problem with desired disturbance attenuation.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.406-413
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• 2007

This paper proposes a self-recurrent wavelet neural network(SRWNN) based adaptive backstepping control technique for the robust steering control of autonomous underwater vehicles(AUVs) with unknown model uncertainties and external disturbance. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the steering model of AUV. The adaptation laws for the weights of SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for the on-line control of AUV. Finally, simulation results for steering control of an AUV with unknown model uncertainties and external disturbance are included to illustrate the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1089-1093
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• 2008

This paper presents a robust state observer design for a class of Lipschitz nonlinear systems with time delay and external disturbance. Sufficient conditions on the existence of the proposed observer are characterized by linear matrix inequalities. It is also shown that the proposed observer design can reduce the effect on the estimation error of external disturbance up to the prescribed level in spite of the existence of time delay. Finally, a numerical example is provided to verify the proposed design method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.199-203
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• 1997

In this paper is proposed a new direct adaptive fuzzy controller that dan ve applied for tracking control of a class of uncertain nonlinear SISO systems. It is shown that, in the presence of the perturbations such as fuzzy approximation error and external disturbance, boundedness of all the signals in the system is ensured, while under the assumption of no perturbations, the stability of the overall system in guaranteed. Also, the concept of persistent excitation in the adaptive fuzzy control systems is introduced to guarantee the convergence and the boundedness of adaptation parameter in the proposed controllers. Simulation example shows the effectiveness of the proposed method in the presence of fuzzy approximation error and external disturbance.

• Tribology and Lubricants
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• v.15 no.1
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• pp.68-76
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• 1999

This paper presents the nonlinear characteristics of the oil lubricated hydrodynamic journal bearing. The traditional approach is to characterize the behavior and performance of fluid film hydrodynamic journal bearings by means of linearized bearing analysis. The objective of this paper is to examine the nonlinear characteristics of the journal bearing when an external sinusoidal shock is given to the system. The oil film force is obtained by solving the finite width Reynolds equation at each time step by the solution of the column method. Frequency response function and journal orbit obtained from both linear and nonlinear bearing simulations are compared with each other.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.93-95
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• 2006

In many control system applications, the system designed must not only satisfy the damping and accuracy specifications, but the control must also yield performance that is robust to external disturbance and parameter variations. We have shown that feedback in conventional control systems has the inherent ability of reducing the effects of external disturbance and parameter variations. Unfortunately, robustness with the conventional feedback configuration is achieved only with a high loop gain, which is normally detrimental to stability. The design of intelligent, autonomous machines to perform tasks that are dull, repetitive, hazardous, or that require skill, strength, or dexterity beyond the capability of humans is the ultimate goal of robotics research. This paper prove the robust control using Analog Adaptive Resonance Theorv(ART2) Algorithm about case study.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.11a
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• pp.160-166
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• 1999

Nonlinear characteristics of the hydrodynamic journal bearing with circumferentially groove are analyzed numerically considering cavitation region, when an external sinusoidal shock is given to the system. The oil film force is obtained by solving the finite width universal Reynolds equation at each time step. Frequency response function and journal orbit obtained from both linear and nonlinear bearing simulations are compared with each other. The vibration response of the journal is different from the expectation obtained from the linear analysis as increase the vibration amplitude of external disturbance. Therefore, the linear theory is not adequate, and the nonlinear calculation such as used in this research is needed to design safety rotor systems.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.254-262
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• 2008

In this paper, we propose an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for full dynamics of nonlinear flight systems. It is assumed that the model uncertainties such as structured and unstrutured uncertainties, and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate the model uncertainties of nonlinear flight systems, and an adaptive DSC technique is extended for the disturbance attenuation of nonlinear flight systems. All weights of SRWNNs are trained on-line by the smooth projection algorithm. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance nom external disturbances can be obtained. Finally, we present the simulation results for a nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.