• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.11
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• pp.394-403
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• 1983

This paper discusses a model reference adaptive control for a multi-input multi-output continuos system in matrix fraction description. The controller is of Monopoli-Narendra type with a time-varying gain matrix in the parameter adaptation law. The transfer matrix of the given plant with an adjustable controller is made to approach to that of the reference model asymptotically. It is shown that, under some plausible assumptions such as on the knowlidge of an interactor matrix, the algorithm for a single-input single-output system can be appropriately extended to a multi-input multi-output system. The convergence of an adaptation law is estavlished with some stability theory and stability of the overall system is asserted by an analytical investigation.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.809-817
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• 2018

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.65-72
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• 2001

Generally, it is said that control of the inertia system is to track the reference input quickly while suppressing the vibration due to the system itself. In this case, the difficulty fur designing a controller is caused by modeling uncertainty and parameter variation. The purpose of this paper is to propose a design method to suppress the vibration of three-mass inertia system based on the LMI theory. That is, the generalized plant model by which we can cope with conservativeness of the existing H$_{*}$ theory is proposed and analyzed in terms of LMI. The results of simulation fur the three-mass inertia system show that the proposed design approach is quite effective under the given situations.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.559-563
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• 1991

Permanent magnet synchronous motor (PMSM) is receiving increased attention for servo drive applications in recent years because of its high torque to inertia ratio, superior power density and high efficiency. Vector-controlled PMSM has the same operating characteristics as separately excited dc motor. The drive system of servo motor is requested to have an accurate response for the speed reference and a quick recovery for the disturbance such as load torque. However the dynamics of PMSM drive change greately by parameter variations. Morever, when the unkown and inaccessible disturbances are imposed on PMSM, the drive system is given a significant effect by them. As a result, the drive system with both a fast drive performance and a reduced sensitivity to parameter variations is requested. In this paper, the robust control system of PMSM with torque feedforward using load torque observer is presented. In the proposed system, load torque is estimated by the reduced order observer, and the robust control system against load torque variation is realized using the torque feedforward. Moreover, the design of speed controller with the torque observer is discussed. Simulation results show that the proposed method is effective for suppression of parameter variations and load disturbance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1648-1654
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• 2016

This paper analyzes complex vector current control for the enhanced cross-coupling compensation in accordance with parameter variation in grid-connected inverter system, and verifies through simulation and experiment. Complex vector current control is performed in the synchronous reference frame through d-q transformation. It generates cross-coupling components with rotating nominal angular frequency. In general, cross-coupling elements are compensated by decoupling terms added to output of conventional decoupling PI controller. But, it is impossible to compensate them perfectly which transient response is especially deteriorated such as large overshoot and slow tracking, when variation of grid impedance or measurement error occurs. However, complex vector current control can improve stability and response characteristic of current control regardless of the situation as before. Decoupling controller and complex vector controller are represented through complex forms, and these controllers are analyzed by using frequency response in s-domain, respectively. It is verified that complex vector controller has more superior response characteristic than decoupling controller through MATALB, PSIM and experimental in 5kW grid-connected inverter when L filter parameter is varied from 1.1mH to increase double, 2.2mH.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• Advances in nano research
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• v.6 no.3
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• pp.219-242
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• 2018

In this study, static bending of an edge cracked cantilever nanobeam composed of functionally graded material (FGM) subjected to transversal point load at the free end of the beam is investigated based on modified couple stress theory. Material properties of the beam change in the height direction according to exponential distributions. The cracked nanobeam is modelled using a proper modification of the classical cracked-beam theory consisting of two sub-nanobeams connected through a massless elastic rotational spring. The inclusion of an additional material parameter enables the new beam model to capture the size effect. The new non-classical beam model reduces to the classical beam model when the length scale parameter is set to zero. The considered problem is investigated within the Euler-Bernoulli beam theory by using finite element method. In order to establish the accuracy of the present formulation and results, the deflections are obtained, and compared with the published results available in the literature. Good agreement is observed. In the numerical study, the static deflections of the edge cracked FGM nanobeams are calculated and discussed for different crack positions, different lengths of the beam, different length scale parameter, different crack depths, and different material distributions. Also, the difference between the classical beam theory and modified couple stress theory is investigated for static bending of edge cracked FGM nanobeams. It is believed that the tabulated results will be a reference with which other researchers can compare their results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.913-921
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• 2009

This paper suggests a deign method of the model-following $H{\infty}$ control system having robust performance. This $H{\infty}$ control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by $H{\infty}$ control theory. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust performance of closed-loop system. The effectiveness of this $H_{\infty}$ control system is verified by computer simulation.

• Aerospace Engineering and Technology
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• v.2 no.1
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• pp.22-28
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• 2003

This paper presents a method for estimating static aerodynamic derivatives by analyzing data obtained from the flying quality evaluation test of a small canard aircraft. The aerodynamic derivatives extracted from maximum likelihood estimation method and from the proposed method in this paper are compared in the same polt. Reliable static aerodynamic derivatives were extracted from a limited number of the flight tests by the proposed method. The parameter data obtained from this method can be used as reference for the conventional parameter identification methods such as maximum likelihood estimation method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.67-73
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• 2006

In this paper, a reconfigurable model following flight control method is proposed based on direct adaptive scheme using parameter estimation. Adaptive control scheme updates the control gains to make the system output follow the reference output even when fault occurs. By adopting the frequency domain parameter estimation method, system changes by the fault can be estimated. Recursive Fourier transformation is used for system identification. Using recursive Fourier transform, the proposed adaptive control algorithm guarantees the system stability and improves the system characteristics. To evaluate the performance of proposed control method, numerical simulations are performed.