• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.11
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• pp.1254-1264
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• 2008

This paper suggests an extended memory polynomial model that improves accuracy in modeling memory effects of RF power amplifiers(PAs), and verifies effectiveness of the suggested method. The extended memory polynomial model includes cross-terms that are products of input terms that have different delay values to improve the limited accuracy of basic memory polynomial model that includes the diagonal terms of Volterra kernels. The complexity of the memoryless model, memory polynomial model, and the suggested model are compared. The extended memory polynomial model is represented with a matrix equation, and the Volterra kernels are extracted using least square method. In addition, the structure of digital predistorter and digital signal processing(DSP) algorithm based on the suggested model and indirect learning method are proposed to implement a digital predistortion linearization. To verify the suggested model, the predicted output of the model is compared with the measured output for a 10W GaN HEMT RF PA and 30 W LDMOS RF PA using 2.3 GHz WiBro input signal, and adjacent-channel power ratio(ACPR) performance with the proposed digital predistortion is measured. The proposed model increases model accuracy for the PAs, and improves the linearization performance by reducing ACPR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.681-684
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• 2015

Power amplifier is an essential component for transmitting signals to a remote receiver in wireless communication systems. Power amplifier is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and decreases the transmit signal quality. To linearize power amplifiers, many techniques have been developed so far. Among the techniques, digital pre-distortion is known as the most cost and performance effective technique. However, the linearization performance falls down abruptly when the power amplifier operates in its saturation region. This is because of the severe nonlinearity. To relieve this problem, this paper proposes a new adaptive predistortion technique. The proposed technique controls the adaptive algorithm based on the power amplifier input level. Specifically, for small signals, the adaptive predistortion algorithm works normally. On the contrary, for large signals, the adaptive algorithm stops until small signals occur again. By doing this, wrong coefficient update by severe nonlinearity can be avoided. Computer simulation results show that the proposed method can improve the linearization performance compared with the conventional digital predistortion algorithms.

• Structural Engineering and Mechanics
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• v.28 no.1
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• pp.89-105
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• 2008

The paper presents a study on the effects of soil-structure-interaction (SSI) on the performance of the compliant liquid column damper (CLCD) for the seismic vibration control of short period structures. The frequency-domain formulation for the input-output relation of a flexible-base structure with CLCD has been derived. The superstructure has been modeled as a linear, single degreeof-freedom (SDOF) system. The foundation has been considered to be attached to the underlying soil medium through linear springs and viscous dashpots, the properties of which have been represented by complex valued impedance functions. By using a standard equivalent linearization technique, the nonlinear orifice damping of the CLCD has been replaced by equivalent linear viscous damping. A numerical stochastic study has been carried out to study the functioning of the CLCD for varying degrees of SSI. Comparison of the damper performance when it is tuned to the fixed-base structural frequency and when tuned to the flexible-base structural frequency has been made. The effects of SSI on the optimal value of the orifice damping coefficient of the damper has also been studied. A more convenient approach for designing the damper while considering SSI, by using an established model of a replacement oscillator for the structure-soil system has also been presented. Finally, a simulation study, using a recorded accelerogram, has been carried out on the CLCD performance for the flexible-base structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.24-33
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• 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 Power Electronics
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• v.18 no.3
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• pp.766-777
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• 2018

In this paper, a sliding mode and proportional plus integral (SM-PI) control combined with self-sustained phase shift modulation (SSPSM) for LLC resonant converters is presented. The proposed control scheme improves the transient response while preserving good steady-state performance. An averaged large signal model of an LLC converter with the ZVS modulation technique is developed for the SM control design. The sliding surface is obtained based on the input-output linearization concept. A system identification method is adopted to obtain the transform function of the LLC resonant converter, which is used to design the PI control. In order to reduce the inherent chattering problem in the steady state, the combined SM-PI control strategy is derived with fuzzy control, where the SM control is responsive during the transient state while the PI control prevails in the steady state. The combination of SSPSM and the SM-PI control provides ZVS operation, robustness and a fast transient response against step load variations. Simulation and experimental results validate the theoretical analysis and the attractive features of the proposed scheme.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1066-1074
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• 1990

In this paper, we attempt to control induction motors with high power efficiency as well as high dynamic performance by utilizing the recently developed theories : singular perturbation technique and noninteracting feedback control. Our controller consists of three subcontrollers` a saturation current controller, a decoupling controller, and a well-known flux simulator. The decoupling controller decouples rotor speed (or motor torque) and rotor flux linearly. Our controller does not need the rotor resistance that varies widely with the machine temperature. To illuminate the practical significance of our results, we present simulation and experimental results as well as mathematical performance analysis.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.307-310
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• 2006

We consider the problem of constructing observers for nonlinear systems with unknown inputs. It is shown that under some conditions, there exists an observer estimating the states of nonlinear systems with unknown inputs. Nonlinear observer design method using observer error linearization and the design technique of unknown input observer(UIO) for linear systems are used to derive conditions. Some illustrative examples are included. In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller.The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system

• Journal of electromagnetic engineering and science
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• v.7 no.2
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• pp.91-95
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• 2007

In this paper, a new linearization method has been proposed for a CMOS low noise amplifier(LNA) using the Post IM3 Compensator. The fundamental operating theory of the proposed method is to cancel the IM3 components of the LNA output signal by generating another IM3 components, which are out-phase with respect to that of the LNA, from the Post IM3 Compensator. A single stage common-source LNA has been designed to verify the linearity improvement of the proposed method through $0.13{\mu}m$ RF CMOS process for WiBro system. The designed LNA achieves +7.8 dBm of input-referred 3^{rd}$-order intercept point (IIP3) with 13.2 dB of Power Gain, 1.3 dB of noise figure and 5.7mA @1.5V power consumption. IIP3 is compared with a conventional single stage common-source LNA, and it shows IIP3 is increased by +12.5 dB without degrading other features such as gain and noise figure.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.641-646
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• 2014

In this paper, we propose a controller for a ball and beam system which reduces the measurement error effect under AC and DC noise. The ball and beam system measures data through a sensor. If sensor noise is included in a controller via the feedback channel, the signal is distorted and the entire system cannot work normally. Therefore, some appropriate action for the measurement error effect is essential in the controller design. Our controller is equipped with a gain-scaling factor and a compensator to reduce the effect of measurement error in the feedback signal. Effectively, our proposed controller can reduce the AC and DC noise of a feedback sensor. We analyze the proposed controller by Laplace transform technique and illustrate the improved control performance via an experiment for a ball and beam system.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.117-127
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.