• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.37 no.3
• /
• pp.28-34
• /
• 2000

In this paper, we derive a spectral function and a new impedance profile of non-uniform tapered transmission lines by applying the Fourier transform to a linearized Riccati equation. We compensate the error which is from a linearized Riccati equation by adding a Taylor series to the impedance profile. Added terms remove discontinuities In the impedance profile at both ends of the non-uniform section. We show that a calculated spectrum approaches to a target spectrum of filter by an iterative method and numerical examples are given to illustrate the role of the phase function. As the design method which is shown in present paper provides a excellent adaptability for the design of non-uniform tapered transmission lines, the present method can be applied to design filters and impedance matching circuits with various passband characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.10A
• /
• pp.935-942
• /
• 2006

The performance of ROF systems can be severely degraded due to nonlinear effects in the channel. Also, Orthogonal Frequency Division Multiplex(OFDM), as a standard for broadband wireless and mobile internet networks, is being proposed for deployment with ROF systems to facilitate the total performance of a system. In this paper, at first, the performance of the OFDM-based RoF system with a Mach-Zehnder(MZ) modulator distortion effects has been analyzed at 5.8GHz. Evaluation of mean-squared error of the proposed OFDM-RoF system was carried out to compare with the conventional single carrier system based RoF link after the modulator distortion case and also for fixed signal to noise ratio(SNR) of 20dB using undistorted OFDM signal. Nominal and offset baising pre-distortion techniques are applied in proposed system to linearize the OFDM-RoF link. Finally, a comparison between the aforementioned pre-distortion techniques applied showed important observation in terms of distortion-free dynamic range and SNR to choose offset pre-distortion technique for our proposed system.

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

• Journal of the Korean Society of Propulsion Engineers
• /
• v.3 no.1
• /
• pp.24-33
• /
• 1999

For performance prediction and diagnostics of gas turbine engines, linear and non-linear gas path analysis are applied. In order to find optimal instrument parameters to detect the physical faults such as (outing, erosion and corrosion, non-linear gas path analysis is used. A typical industrial gas turbine engine, TB5000, is used to study the effect of physical faults on engine performance. Through comparison of RMS error between linear and non-linear gas path analysis, the optimal instrument parameters can be defined. As a result, it is found that the linear GPA has the level of error introduced by the assumption of the linear mode: can be of the same order of magnitude as the fault being soughtwhile the non-linear GPA can be solved the non-linear relationships between dependent and independent parameters using an iterative method such as the Newton-Raphson method with sufficient accuracy.

• Korean Journal of Optics and Photonics
• /
• v.17 no.3
• /
• pp.216-222
• /
• 2006

We propose the use of the Gaussian-curve fitting algorithm for the improvement of measurement accuracy in wavelengthscanned Fabry-Perot filter based demodulation systems. The peak locations of FBG sensors were calculated from the fitted curves rather than from distorted PD profiles, resulting in much better measurement accuracy than that of the highest-peak search algorithm. Also, the algorithm was proved to minimize measurement uncertainty of spectrally-distorted grating sensors. From our experimental results, a temperature resolution as small as ${\sim}0.3^{\circ}C$ was readily achieved by use of the Gaussian-curve fitting algorithm whereas the highest-peak search algorithm gave a temperature resolution larger than ${\sim}4^{\circ}C$.

• Journal of Advanced Navigation Technology
• /
• v.5 no.1
• /
• pp.19-25
• /
• 2001

In this study an analysis on flight characteristics and flight control methods for a wing in ground effect vehicle is made. In order to closely view its nonlinearity a few limit cycles are examined and related to the characteristics of the linearized systems. Several flight control methods are compared for the cruise mode with initial height error and command tracking mode of ascending, cruise, and descending. In comparison performance and the implementation aspects are examined. For the possible control inputs, combinations of elevator, thrust, and flap are considered and LQR-based output command tracking scheme is applied in the control system design.

• Journal of IKEEE
• /
• v.22 no.1
• /
• pp.110-120
• /
• 2018

In this paper, we apply the input-output linearization technique to tracking the follow-up trajectory r(t) in the ball-beam system. There exist system disturbance and various uncertainties, the conventional input-output linearization based control yields some noticeable errors in tracking performance. As a result, a new robust control technique for the uncertainty of the system was proposed and its improved performance verified through simulation and experimental results. So, more realistic system model is obtained with unmatched uncertainties and disturbance. Then, in order to improve the control performance, a new optimal bang-bang control input is additionally added.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.32 no.4
• /
• pp.24-33
• /
• 2004

In this paper, the helicopter flight control system using online adaptive neural networks which have the universal function approximation property is considered. It is not compensation for modeling errors but approximation two functions required for feedback linearization control action from input/output of the system. To guarantee the tracking performance and the stability of the closed loop system replaced two nonlinear functions by two neural networks, weight update laws are provided by Lyapunov function and the simulation results in low speed flight mode verified the performance of the control system with the neural networks.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.2
• /
• pp.93-100
• /
• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.1
• /
• pp.129-137
• /
• 2017

In this paper, we propose a digital controller design methodology for an LLC resonant converter which has been widely used due to the advantages of low switching loss and high efficiency. We establish a mathematical model of an LLC resonant converter using the extended describing function concept and propose a controller design method based on the Ziegler Nichols control parameter tuning criteria. The voltage controller of an LLC resonant converter is designed based on the derived small signal model and the performance of the controller is verified by MATLAB simulations. The validity and the control performance of the designed voltage controller for the LLC resonant converter is analyzed through some simulations for the case of load variations and circuit modeling errors.