• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.9
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• pp.45-52
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• 2006

In this study, a nonlinear control by feedback linearization method, one of nonlinear control schemes based on the nonlinear model, is proposed to suppress the flutter of a supersonic composite panel using piezoelectric materials. Most of the previous panel flutter controllers are the LQR(Linear Quadratic Regulator) which is based on the linear model. A nonlinear feedback linearizing controller proposed in this study considers the nonlinear characteristics of the system model. We use the actuator implemented by piezoceramic PZT. Using the principle of virtual displacements and a finite element discretization with the conforming four-node rectangular element, we first derive the discretized dynamic equations of motion, which are transformed into a nonlinear coupled-modal equations of motion of state space form. The effectiveness of the proposed method is also compared with the LQR based on the linear model through numerical simulations in the time domain using the Newmark method.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.700-705
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• 2012

This paper addresses an intelligent digital redesign (IDR) technique for observer-based output-feedback control systems, in order to efficiently convert a pre-designed Takagi-Sugeno fuzzy model-based analog controller into a sampled-data one in the sense of state matching. A delta operator is used to get an asymptotic relation between the analog and the sampled-data control systems. The IDR problem is viewed as a minimization problem of the norm distances between linear operator to be matched. The condition is represented as linear matrix inequalities, and the separation principle on the IDR is shown.

• Journal of IKEEE
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• v.14 no.3
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• pp.182-189
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• 2010

A new Adaptive neural state-feedback controller for the fully nonaffine pure-feedback nonlinear system are presented in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controller requires no backstepping design procedure. Avoiding backstepping makes the controller structure and stability analysis considerably simple. The proposed controller employs only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller. Simulation examples demonstrate the efficiency and performance of the proposed approach.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.214-221
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• 1998

A new control approach using neural network for the robust position control of a BRUSHLESS direct drive(BLDD) motor is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust BLDD motor system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system will be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained by error back-propagation at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. In addition, the robustness is also obtained without affecting overall system response.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.372-384
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• 1993

The inverted pendulum system has interesting and challenging problems related to robotics and rocket attitude control view of both control theory and applications. Generally approximately linearized plant models are employed to control the system. In this paper a recently developed control theory based on differentiable manifold theory is used to control the inverted pendulum system which is typically nonlinear. First, the nonlinear model is transformed into the approximate feedback linearized system by nonlinear state feedback. Secondly, the linear controller is designed using the pole-placement method for the approximate feedback linearized plant model, the output of which are finally inverse-transformed to yield the control input to the actual system of the inverted pendulum. The proposed method is evaluated by the computer simulation to compare with the 3rd order linearization model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.3 s.108
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• pp.283-290
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• 2006

This study is concerned with static and sinusoidal disturbance rejection for a single periodic input disturbance with known period. In the area of active elimination of a disturbance force, the control input should have two different kinds of gains: one is to deliver a stable control and the other is a force component to cancel the external disturbance force. In this paper we employ a simple state feedback control law to make the balance beam stable and employ a linear observer to estimate the states which represent the external disturbance force components. Simulation results verify our proposed control method to reject a static and sinusoidal disturbance force.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.542-544
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• 2020

최근 분산전원 시스템의 증가로 인해 계통연계 인버터의 사용이 꾸준하게 증가해 왔다. 계통연계 인버터의 제어를 위해 많이 사용되는 PI 제어기는 구조가 간단하여 제어기 구성이 쉽다는 장점이 있지만 계통 전압에 예상치 못한 전압 외란이 발생할 경우 전류 품질이 떨어지는 단점을 가지고 있다. 이를 극복하기 위해 본 논문에서는 LCL 필터를 사용하는 계통연계 인버터의 상태공간 모델을 이용하여 공진제어기와 적분제어기가 결합된 전 상태궤환 제어기법을 제시한다. 또한 계통외란과 주파수 변동으로 인해 발생하는 주파수 검출성능 향상을 위해 SOGI-PLL을 사용하여 시스템의 안정성을 보장한다. 제안된 기법의 타당성과 성능이 PSIM 시뮬레이션을 통하여 입증된다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.1-9
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• 2000

In this paper, we design a robust output feedback controller for robot manipulators with bounded parametric uncertainties using high-gain observer. The proposed control scheme with integral action improves tracking error due to limit of the robust feedback gains. High-gain observer is used to solve the noise problem with the joint velocity measurement. This controller avoids the limitation on the variation of unknown parameters and guarantees the uniformly ultimate boundedness of the closed-loop system. The performance of the proposed method is demonstrated by simulation on a 2-link manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.219-224
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• 1988

A decentralised computational procedure is proposed for the optimal feedback gain matrix of large-scale discrete-time systems with time-delays. The constant feedback gain matrix is computed from the optimal state and input trajectries obtained hierarchically by the interaction prediction method. All the calculation in this approach are done off-line. The resulting gains are optimal for all the initial conditions. The interaction prediction method is applied to time-delay large-scale systems with general structures by extending the dimensions of coupling matices. A numerical exampie illustrates the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1040-1044
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• 1992

This paper presents an algebraic approach for finding a dynamic state feedback controller when the linear multi-input system with delays in both state and input is controllable. In the time-delay case, controllability of the system does not always imply that system is cyclizable. Therefore, reduced order augmentation systems which is cyclizable as the time-varying case are considered. It is possible to construct feedback contorl systems by using single-input methods.