• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.243-250
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• 2010

As the wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is how to efficiently operate the wind turbines in a wide range of wind speeds. Compared to fixed speed turbines, variable speed wind turbines feature higher energy yields, lower component stress and fewer grid connection power peaks. Generally, measurement of wind speed is required for the control of variable speed wind turbine system. However, wind speed measured by anemometers is not accurate owing to various reasons. In this work, a new control algorithm for variable speed wind turbine system based on Kalman filter which can be used for the estimation of wind speed and artificial neural network which can generate optimum rotor speed is proposed. Also, to verify the feasibility of the proposed scheme, various simulation studies are carried out by using Simulink in Matlab.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.279-284
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• 2014

This paper proposes a optimum design method for the Fuzzy PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV). Since an attraction type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the methods designed by conventional controllers. In the paper, the Fuzzy PID controller with fixed parameters are applied and then the optimum parameters of fuzzy PID controller are selected by genetic algorithm. For the fitness function of genetic algorithm, the performance index of PID controller is used. To verify the performance of the proposed method, we used Matlab/simulink model of Maglev and compared the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.

• Journal of Drive and Control
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• v.14 no.2
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• pp.16-22
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• 2017

This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.

• Journal of Drive and Control
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• v.14 no.2
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• pp.30-36
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• 2017

This paper presents a sliding mode observer-based fault detection algorithm for steering inputs of an all-terrain crane. All-terrain cranes with multi-axles have several steering modes for various working purposes. Since steering angles at the other axles except the first wheel are controlled by using the information of steering angle at the first wheel, a reliable signal of the first axle's steering angle should be secured for the driving safety of cranes. For the fault detection of steering input signal, a simplified crane model-based sliding mode observer has been used. Using a sliding mode observer with an equivalent output injection signal that represents an actual fault signal, a fault signal in steering input was reconstructed. The road steering mode of the crane's steering system was used to conduct performance evaluations of a proposed algorithm, and an arbitrary fault signal was applied to the steering angle at the first wheel. Since the road steering mode has different steering strategies according to different speed intervals, performance evaluations were conducted based on the curved path scenario with various speed conditions. The design of algorithms and performance evaluations were conducted on Matlab/Simulink environment, and evaluation results reveal that the proposed algorithm is capable of detecting and reconstructing a fault signal reasonably well.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.694-702
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• 2014

One of the most important devices in an underwater vessel is a propulsion system. It should be a quiet and efficient system for stealthy operations in the large mission area. Hence lead-acid battery system has been used to supply the energy to electric motor. Recent technological developments and improvements, such as polymer electrolyte membrane(PEM) fuel cell and lithium polymer battery and have created the potential to improve overall power and propulsion performance. An underwater vessel always starts their mission with a limited energy and is not easy to refuel. Therefore design of energy elements, such as fuel cell and battery, and their load distribution are important to increase the maximum operating time of underwater vessel. In this paper, the lead-acid battery/PEM fuel cell and lithium polymer battery/PEM fuel cell were suggested as propulsion system and their performances were analyzed by modeling and simulation using Matlab/Simulink. Each model concentrated on representing the characteristics of energy element depending on demand current. As a result the effect of load distribution between battery and fuel cell was evaluated and the operation time of each propulsion system was able to be estimated exactly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1879-1885
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• 2017

This paper discusses the trajectory tracking system of unmanned ground vehicles based on predictive control. Because the unmanned ground vehicles can not satisfactorily complete the path tracking task, highly efficient and stable trajectory control system is necessary for unmanned ground vehicle to be realized intelligent and practical. According to the characteristics of unmanned vehicle, this paper built the kinematics tracking models firstly. Then studied algorithm solution with the tools of the optimal stability analysis method and proposed a tracking control method based on the model predictive control. The controller used a kinematics-based prediction model to calculate the predictive error. This controller helps the unmanned vehicle drive along the target trajectory quickly and accurately. The designed control strategy has the true robustness, simplicity as well as generality for kinematics model of the unmanned vehicle. Furthermore, the computer Simulink/Carsim results verified the validity of the proposed control method.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.309-317
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• 2000

This paper presents the switching angle and voltage to maximize torque/efficiency and minimize torque ripple in the 4-phase 6-poles Switched Reluctance Motor(SRM). SRM drive has high saturation and nonlinear characteristics of inductance. So we cannot hard to find optimal condition by using analytic method. Therefore it is hard to find the operating the switching angle and voltage through the approximated analysis and computer simulation by using SIMULINK according to the speed and torque required by load. From the results, we can say that the optimum average voltage is determined by the load only and the speed is determined by the optimum turn-on/off angle only. And the maximum efficiency and minimum torque ripple depend on switching angle, not on voltage. And then one-chip microcontroller controls the switching angle and voltage of an asymmetrical inverter in the SRM driver. This drive method, which is expect that the driving methods, which are maximizing torque/efficiency and minimizing torque ripple, will be suitable for the electric vehicle, the industrial application and household appliances.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1964-1980
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• 2016

This paper presents a new simplified harmonics extraction algorithm based on the synchronous reference frame (SRF) for an indirect current controlled (ICC) three-level neutral point diode clamped (NPC) inverter-based shunt active power filter (SAPF). The shunt APF is widely accepted as one of the most effective current harmonics mitigation tools due to its superior adaptability in dynamic state conditions. In its controller, the SRF algorithm which is derived based on the direct-quadrature (DQ) theory has played a significant role as a harmonics extraction algorithm due to its simple implementation features. However, it suffers from significant delays due to its dependency on a numerical filter and unnecessary computation workloads. Moreover, the algorithm is mostly implemented for the direct current controlled (DCC) based SAPF which operates based on a non-sinusoidal reference current. This degrades the mitigation performances since the DCC based operation does not possess exact information on the actual source current which suffers from switching ripples problems. Therefore, three major improvements are introduced which include the development of a mathematical based fundamental component identifier to replace the numerical filter, the removal of redundant features, and the generation of a sinusoidal reference current. The proposed algorithm is developed and evaluated in MATLAB / Simulink. A laboratory prototype utilizing a TMS320F28335 digital signal processor (DSP) is also implemented to validate effectiveness of the proposed algorithm. Both simulation and experimental results are presented. They show significant improvements in terms of total harmonic distortion (THD) and dynamic response when compared to a conventional SRF algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.21-28
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• 2010

This paper describes the mathematical model and controller design for Manta-type Unmanned Underwater Test Vehicle (MUUTV) with 6 DOF nonlinear dynamic equations. The mathematical model contains hydrodynamic forces and moments expressed in terms of a set of hydrodynamic coefficients which were obtained through the PMM (Planar Motion Mechanism) test. Based on the 6 DOF dynamic equations, numerical simulations have been performed to analyze the dynamic performances of the MUUTV. In addition, using the mathematical model PID and sliding mode controller are constructed for the diving and steering maneuver. Simulation results show that the control performances of the MUUTV and compared with these of NPS (Naval Postgraduate School) AUV II.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.119-128
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• 2004

With the growing traffic density and increasing comfort requirements, the automation of the drive train will gain importance in vehicles. The automatic clutch actuation relieves the drivers especially in urban driving and stop-and-go traffic conditions. This paper describes the dynamic modeling of a clutch actuator and clutch spring. The dynamic model of the clutch system is developed using MATLAB/Simulink, and evaluated by experimental data using a test rig. This performance simulator is useful to develop the clutch-by-wire (CBW) system for an automated manual transmission (AMT). The electro-mechanical type CBW system is also implemented as an automatic clutch for AMT. The prototype of CBW system is designed and implemented systematically, which is composed of an electric motor, worm gear and slider-crank mechanism. The test rig is developed to perform the basic function test of the automatic clutch, and the developed prototype is validated by the experimental data on the test rig.