• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.4
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• pp.82-91
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• 1997

In this paper, a design method of the boiler-turbine control system in the coal fired power plant is proposed. We need to control electric output and drum pressure and water level in drum to guarantee stable operation and save energy for generating electricity and decrease air pollution in the boiler-turbine system. This boiler-turbine control system is composed of reference model part and model following part. The multivariable boiler-turbine system is separated into 3 SISO(Single Input Single Output) systems applying the concept of relative gain matrix. Each 3 reference models for separated boiler-turbine system are composed of 1st order nominal plant and hysteresis integral control system and they make good dy¬namic response with no overshoot and fast rising time. Each fuzzy controller to follow as close as possible to the response of each reference model is designed. The robustness and the good tracking property can be achieved using 5150 fuzzy controllers when there are modeling errors, disturbances and parameter pertur¬bations. The effectiveness of the proposed design method is verified through simulations.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1455-1468
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• 2016

This paper presents a grid-connected dual stator-winding induction generator (DWIG) wind power system suitable for wide wind speed ranges. The parallel connection via a unidirectional diode between dc buses of both stator-winding sides is employed in this DWIG system, which can output a high dc voltage over wide wind speed ranges. Grid-connected inverters (GCIs) do not require booster converters; hence, the efficiency of wind energy utilization increases, and the hardware topology and control strategy of GCIs are simplified. In view of the particularities of the parallel topology and the adopted generator control strategy, we propose a novel excitation-capacitor optimization solution to reduce the volume and weight of the static excitation controller. When this excitation-capacitor optimization is carried out, the maximum power tracking problem is also considered. All the problems are resolved with the combined control of the DWIG and GCI. Experimental results on the platform of a 37 kW/600 V prototype show that the proposed DWIG wind power system can output a constant dc voltage over wide rotor speed ranges for grid-connected operations and that the proposed excitation optimization scheme is effective.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.85-90
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• 2013

PID control for unstable processes with time delay is not easy to apply because of unstability due to the poles existing on left-hand side in s-plane and the effect of time delay. In this paper, the authors consider the PID controller design technique in case of predefining overshoot or rising time by designer according to control environment. To deal with constraint problem like this, in this paper, the RCGA incorporating the penalty strategy is used. This is the method that if the RCGA violates given constraints, the defined penalty function is summed to the evaluation function depending on the severity and then the given constraint problem is converted to non-constraints optimization problem. The proposed method is applied to the unstable FOPTD(First Order Plus Time Delay) system and simulations are accomplished to illustrate the set-point tracking performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.88-97
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• 2013

This paper presents a robust air-to-fuel ratio (AFR) control algorithm for managing exhaust gas recirculation (EGR) systems. In order to handle production tolerance, deterioration and parameter-varying characteristics of the EGR system, quantitative feedback theory (QFT) is applied for designing the robust AFR control algorithm. A plant model of EGR system is approximated by the first order transfer function plus time-delay (FOPTD) model. EGR valve position and AFR of exhaust gas are used as input/output variables of the plant model. Through engine experiments, parameter uncertainty of the plant model is identified in a fixed engine operating point. Requirement specifications of robust stability and reference tracking performance are defined and these are fulfilled by the following steps: during loop shaping process, a PID controller is designed by using a nominal loop transmission function represented on Nichols chart. Then, the frequency response of closed-loop transfer function is used for designing a prefilter. It is validated that the proposed QFT-based AFR control algorithm successfully satisfy the requirements through experiments of various engine operating points.

• Journal of Energy Engineering
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• v.19 no.2
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• pp.128-135
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• 2010

This paper introduces step by step procedures for the fabrication and operation of an embedded solar tracker. The system presented consists of application software, compactRIO, C-series interface module, analogue input module, step drive, step motor, feedback devices and other accessories to support its functional stability. CompactRIO that has a real-tim processor allows the solar tracker to be a stand-alone real time system which operates automatically without any external control. An astronomical method and an optical method were used for a high-precision solar tracker. CdS sensors are used to constantly generate feedback signals to the controller, which allow a solar tracker to track the sun even under adverse conditions. The database of solar position and sunrise and sunset time was compared with those of those of the Astronomical Applications Department of the U.S. Naval Observatory. The results presented here clearly demonstrate the high-accuracy of the present system in solar tracking, which are applicable to many existing solar systems.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.1-9
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• 2016

In this paper, we propose a new learning control scheme for various walk motion control of biped robot with same learning-base by neural network. We show that learning control algorithm based on the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multi layer back propagation neural network identification is simulated to obtain a dynamic model of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The biped robots have been received increased attention due to several properties such as its human like mobility and the high-order dynamic equation. These properties enable the biped robots to perform the dangerous works instead of human beings. Thus, the stable walking control of the biped robots is a fundamentally hot issue and has been studied by many researchers. However, legged locomotion, it is difficult to control the biped robots. Besides, unlike the robot manipulator, the biped robot has an uncontrollable degree of freedom playing a dominant role for the stability of their locomotion in the biped robot dynamics. From the simulation and experiments the reliability of iterative learning control was illustrated.

• Journal of the Korean Society of Propulsion Engineers
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• v.18 no.2
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• pp.27-34
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• 2014

Buzz margin scheduling and control technique which are suitable to regulate stable and high pressure air in wide range of Mach number are suggested for fixed geometry of a supersonic intake. From the analysis of preceding study, most effective control variable is induced and scheduling law is newly suggested in a real application point of view. The appropriateness of the control law in wide range of Mach number is addressed by numerical simulation of controlled propulsion system. Also, the simulation for stabilization and tracking performances of the controller are studied to investigate the phenomena under flight maneuver and disturbances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.89-92
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• 2005

Using natural speech commands for controlling a human-robot is an interesting topic in the field of robotics. In this paper, our main focus is on the verification of a speaker who gives a command to decide whether he/she is an authorized person for commanding. Among possible dynamic features of natural speech, pitch period is one of the most important ones for characterizing speech signals and it differs usually from person to person. However, current techniques of pitch detection are still not to a desired level of accuracy and robustness. When the signal is noisy or there are multiple pitch streams, the performance of most techniques degrades. In this paper, we propose a two-level approach for pitch detection which in compare with standard pitch detection algorithms, not only increases accuracy, but also makes the performance more robust to noise. In the first level of the proposed approach we discriminate voiced from unvoiced signals based on a neural classifier that utilizes cepstrum sequences of speech as an input feature set. Voiced signals are then further processed in the second level using a modified standard AMDF-based pitch detection algorithm to determine their pitch periods precisely. The experimental results show that the accuracy of the proposed system is better than those of conventional pitch detection algorithms for speech signals in clean and noisy environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.698-707
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• 2017

This paper deals with predictive control methods of mobile robots for reference trajectory tracking control. Predictive control methods using predictive model are known as effective schemes that minimize the future errors between the reference trajectories and system states; however, the amount of real-time computation for the predictive control are huge so that their applications were limited to slow dynamic systems such as chemical processing plants. Lately with high computing power due to advanced computer technologies, the predictive control methods have been applied to fast systems such as mobile robots. These predictive controllers have some control parameters related to control performance. But these parameters have not been optimized. In this paper we employed the genetic algorithm to optimize the control parameters of the predictive controller for mobile robots. The improved performances of the proposed control method are demonstrated by the computer simulation studies.