• 전자공학회논문지S
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• 제34S권9호
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• pp.41-49
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• 1997

In this paper, we describe the algorithm which controls an unknown nonlinear system with disturbance a using multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate an unknown nonlinear system by using of multilayer neural netowrk. WE include a disturbance among the modelling error, and the weight-update rule of multilayer neural network is derived to satisfy Laypunov stability. The whole control system constitutes controller using the feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.463-465
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• 1997

For fast response of the dc output voltage in PWM converter, the relationship of power balance of both the input and output should be introduced to the system modeling. Then, a nonlinear control theory using state feedback linearization is useful to control the system. By nonlinear control, the voltage response can be fast, so the size of the output filter capacitor can be reduced as long as the same response is kept. The validity of the proposed scheme is shown from the simulation results.

• Journal of Mechanical Science and Technology
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• 제20권5호
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• pp.591-601
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• 2006

In this paper, we present a new control methodology for perturbed crane systems. Nonlinear crane systems are transformed to linear models by feedback linearization. An inverse dynamic equation is applied to compute the system PD control force. The PD control parameters are selected based on a nominal model and are therefore suboptimal for a perturbed system. To achieve the desired performance despite model perturbations, we construct a neural network auxiliary controller to compensate for modeling errors and disturbances. The overall control input is the sum of the nominal PD control and the neural auxiliary control. The neural network is iteratively trained with a perturbed system until acceptable performance is attained. We apply the proposed control scheme to 2- and 3-degree-of-freedom (D.O.F.) crane systems, with known bounds on the payload mass. The effectiveness of the control approach is numerically demonstrated through computer simulation experiments.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1251-1258
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• 2003

This paper presents a nonlinear robust approach to the slip control problem for a torque converter bypass clutch in a passenger car. The proposed nonlinear robust controller builds upon only the measurements avail-able from inexpensive sensors that are already installed in passenger cars for control. The issue of torque estimation problems for the implementation of the proposed controller is addressed. The stability of the internal dynamics is investigated, upon which a nonlinear robust controller is designed using input-output feedback linearization and Lyapunov redesign technique. The performance of the designed controller is validated by simulation studies.

• 전기학회논문지
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• 제63권11호
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• pp.1594-1601
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• 2014

In this paper, we propose the LQ servo control method for the automatic train control of urban rail vehicle. Structures of the conventional PID control and LQ servo controller are compared in order to demonstrate the simplicity of the proposed controller which doesn't have zeros of the closed loop systems. The energy consumption is dealt with as an object function to be minimized, which consists of the quadratic performance indices for optimal control with the input of the feedback linearization. The effectiveness of the proposed method is shown by the practical example, compared with the conventional PD controller.

• 전기의세계
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• 제26권6호
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• pp.48-54
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• 1977

The object of this work is to study the optimal control strategy of constant speed characteristics for a D.C control motor under influence of disturbance. In the course of the analysis, the linearization and time invariance schemes on motor dynamics are presumed throughout under certain prescribed conditions and the performance measure for optimality is assumed to be quadratic in state and the control effort, with the initial and final time specified. When the motor speed is deviated from a stationary operating point by any external disturbance, the optimal continuous feedback control law is investigated by the application of the calculus of variation and realizability of the required control meachanism is suggested. Finally, the comparative study of the speed reasponses of the motor, with and without the optimal control effort is also presented to confirm the obtained results.

• International Journal of Aeronautical and Space Sciences
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• 제9권1호
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• pp.31-41
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• 2008

This paper deals with the energy saving problem of the follower aircraft in the loose leader-follower formation geometry in which the lateral separation between formation members is more than a wingspan of the leader aircraft. This formation geometry offers no drag benefit, but has a strategic advantage. In the case of loose formation flight, the follower aircraft usually consumes more energy than the leader aircraft because the follower aircraft should use more thrust to maintain given formation geometry, especially during the turning phase from the outside of the leader"s flight path or join-up phase. A formation control scheme based on the energy maneuverability is proposed in this paper. To design the proposed control law, the velocity command is designed using feedback linearization for the horizontal formation geometry and then coverts it to the altitude command using the energy equation. Numerical simulation is performed to verify the effectiveness of the proposed controller.

• International Journal of Aeronautical and Space Sciences
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• 제14권4호
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• pp.379-386
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• 2013

The hemispherical resonator gyroscope is a type of vibratory gyroscope, which can measure angle or angular rate, based on its operating mode. This paper deals with the case when the hemispherical resonator gyroscope is operated in angle measurement mode. In angle measurement mode, the resonator pattern angle precesses, with respect to the external rotation input, by the principle of the Coriolis effect, so that the external rotation can be estimated, by measuring the amount of precession angle. However, this pattern angle drifts, due to the manufacturing error of the resonator. Since the drift effect causes degradation of the angle estimation performance of the resonator, the corresponding drift compensation control should be performed, to enhance the estimation performance. In this paper, a mathematical model of the hemispherical resonator gyro is first introduced. By using the mathematical model, a nonlinear observer for imperfection parameter estimation, and the corresponding compensation controller are designed to operate hemispherical resonator gyros, as angle measurement sensors.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 F
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• pp.1892-1895
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• 1998

In this paper, a new 3-phase PWM converter power control algorithm is proposed using feedback linearization for the regulation of the active and reactive power demanded by load side. The direct power control can be realized through the proposed control scheme, cancelling out d-q axis coupling terms and nonlinear effects between inputs and states. The actual experimental results prove the feasibility of the proposed nonlinear power controller.

• 전자공학회논문지B
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• 제33B권7호
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• pp.32-39
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• 1996

In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural netowrk can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural netowrk. The weights on the hidden layer of multilayer neural network are updated by gradient method. The weight-update rule on the output layer is derived to satisfy lyapunov stability. Also, we obtain secondary controller form deriving step. The global control system consists of controller using feedback linearization method and secondary controller is order to satisfy layapunov stability. The proposed control algorithm is verified through computer simulation.