• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.1
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• pp.18-27
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• 2002

This paper presents an implementation of digital high-performance speed sensorless control system of an induction motor drives with Direct Torque Control(DTC). The system consists of closed loop stator flux and torque observer, speed and torque estimators, two hysteresis controllers, an optimal switching look-up table, IGBT voltage source inverter, and TMS320C31 DSP controller board. The stator flux observer is based on the combined current and voltage model with stator flux feedback adaptive control for wide speed range. The speed estimator is using the model reference adaptive system(MRAS) with rotor flux linkages for speed turning signal estimation. In order to prove the suggested speed sensorless control algorithm, and to obtain a high-dynamic robust adaptive performance, we have some simulations and actual experiments at low(20rpm) and high(1000rpm) speed areas. The developed speed sensorless system are shown a good speed control response characteristic, and high performance features using 2.2[kW] general purposed induction motor.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.17-20
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• 1996

An adaptive current control scheme of a permanent magnet (PM) synchronous motor with the simultaneous estimation of the magnitude of the flux linkage and stator resistance is proposed. The adaptive parameter estimation is achieved by a model reference adaptive system (MRAS) technique. The adaptive laws are derived by the Popov's hyperstability theory and the positivity concept. The predictive control scheme is employed for the current controller with the estimated parameters. The robustness of the proposed current control scheme is compared with the conventional one through the computer simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.946-961
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• 2004

A new adaptive controller which combines a model reference adaptive controller (MRAC) and a fuzzy controller is developed for unstable nonlinear time-invariant systems. The fuzzy controller is used to analyze and to compensate the nonlinear time-invariant characteristics of the plant. The MRAC is applied to control the linear time-invariant subsystem of the unknown plant, where the nonlinear time-invariant plant is supposed to comprise a nonlinear time-invariant subsystem and a linear time-invariant subsystem. The stability analysis for the overall system is discussed in view of global asymptotic stability. In conclusion. the unknown nonlinear time-invariant plant can be controlled by the new adaptive control theory such that the output error of the given plant converges to zero asymptotically.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.9 no.3
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• pp.108-112
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• 1984

The motivation in this paper is in obtaining an adaptive observer with simple configuaration and faster adapting speed. The identification and state estimation are seperated to increase the adapting speed of the adaptive observer. The method of identification proposed by Ichikawa is modified. And the adaptive observer is constructed by using the output of state variable filters that are used in identification. Finally, the digital simulation results to the proposed system are presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.5
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• pp.416-422
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• 2016

This paper presents preliminary performance analysis of a satellite formation flying testbed, which is under development by Astrodynamics and Control Laboratory, Department of Astronomy, Yonsei University. A model reference adaptive controller (MRAC) with a first-order reference model is chosen to enhance the response of reaction wheel system which is subject to uncertainties caused by unmodelled dynamics and measurement noise. In addition, an on-line parameter estimation (OPE) technique based on the least square is combined to eliminate the effect of angular measurement noise by estimating the moment of inertia. Both numerical simulations and hardware experiments with MRAC support the effectiveness and applicability of the adaptive control scheme, which maintains the tracking error below $0.25^{\circ}$ for the entire time span. However, the high frequency control input generated in hardware experiment strongly suggests design modifications to reduce the effect of deadzone.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.85-86
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• 2006

In this paper, a nonlinear controller based on adaptive sliding-mode method which has a sliding surface vector including new boundary function is proposed and applied to a two-wheeled voiding mobile robot (WMR). This controller makes the welding point of WMR achieve tracking a reference point which is moving on a smooth curved welding path with a desired constant velocity. The mobile robot is considered in view of a kinematic model and a dynamic model in Cartesian coordinates. The proposed controller can overcome uncertainties and external disturbances by adaptive sliding-mode technique. To design the controller, the tracking error vector is defined, and then the new sliding is proposed to guarantee that the error vector converges to zero asymptotically. The stability of the dynamic system will be shown through the Lyapunov method. The simulations is shown to prove the effectiveness of the proposed controller.

• 한국컴퓨터산업교육학회:학술대회논문집
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• 2003.11a
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• pp.127-133
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• 2003

The data models which express all types of video information physically and logically. and the definition of spatiotemporal relationship of video data objects In This paper, we classifies meta-model for efficient management on spatiotemporal relationship between two objects in video image data, suggests meta-models based on Rambaugh's OMT technique, and expanded user model to apply the adaptive model, established from hyper-media or web agent to VOD. The proposed meta-model uses data's special physical feature: the effects of camera's and editing effects of shot, and 17 spatial relations on Allen's 13 temporal relations, topology and direction to include logical presentation of spatiotemporal relation for possible spatiotemporal reference and having unspecified applied mediocrity.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.73-82
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• 1992

An industrial robot, installed real manufacturing processes an element of the system autmation, can be considered as an uncertain system due to dynamic uncertainties in inertial parameters and varying payloads. Most difficuties in controlling a robot manipulator are caused by the fact that the dynamic equations describing the motions of the manipulator are inherently nonlinear and heavily coupled effects between joints and associated links. Existing robot conrol systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severly limited in range of application, speed of operation and variation of payload. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the desinger. The proposed manipulator studied has two loops, an inner loop of model reference adaptive controller and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstailiy approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in practical working environment, various load variations and parameter uncertainties.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1004-1005
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• 2006

This paper investigates a speed sensorless control of induction motor. The control strategy is based on MRAS (Model Reference Adaptive System) using load-torque observer as a reference model for flux estimation. The speed response of conventional MRAS controller characteristics is affected by variations of load torque disturbance. In the proposed system, the speed control characteristics using a load-torque observer control isn't affected by a load torque disturbance. Simulation results are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor.