• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.457-466
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• 2009

This paper presents efficient parallel genetic algorithm (EPGA) based decomposed network for optimal power flow with various kinds of objective functions such as those including prohibited zones, multiple fuels, and multiple areas. Two coordinated sub problems are proposed: the first sub problem is an active power dispatch (APD) based parallel GA; a global database generated containing the best partitioned network: the second subproblem is an optimal setting of control variables such as generators voltages, tap position of tap changing transformers, and the dynamic reactive power of SVC Controllers installed at a critical buses. The proposed approach tested on IEEE 6-bus, IEEE 30-bus and to 15 generating units and compared with global optimization methods (GA, DE, FGA, PSO, MDE, ICA-PSO). The results show that the proposed approach can converge to the near solution and obtain a competitive solution with a reasonable time.

• Journal of Power Electronics
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• v.14 no.1
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• pp.61-73
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• 2014

Multiphase machines are characterized by high power density, enhanced fault-tolerant capacity, and low torque pulsation. For a voltage source inverter supplied multiphase machine, the probability of load imbalances becomes greater and unwanted low-order stator voltage harmonics occur. This paper deals with the PWM control of multiphase inverters under unbalanced load conditions and it proposes a novel near-five-vector SVPWM algorithm based on the five-phase six-leg inverter. The proposed algorithm can output symmetrical phase voltages under unbalanced load conditions, which is not possible for the conventional SVPWM algorithms based on the five-phase five-leg inverters. The cause of extra harmonics in the phase voltages is analyzed, and an xy coordinate system orthogonal to the ${\alpha}{\beta}z$ coordinate system is introduced to eliminate low-order harmonics in the output phase voltages. Moreover, the digital implementation of the near-five-vector SVPWM algorithm is discussed, and the optimal approach with reduced complexity and low execution time is elaborated. A comparison of the proposed algorithm and other existing PWM algorithms is provided, and the pros and cons of the proposed algorithm are concluded. Simulation and experimental results are also given. It is shown that the proposed algorithm works well under unbalanced load conditions. However, its maximum modulation index is reduced by 5.15% in the linear modulation region, and its algorithm complexity and memory requirement increase. The basic principle in this paper can be easily extended to other inverters with different phase numbers.

• Journal of KSNVE
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• v.6 no.2
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• pp.215-224
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• 1996

Active vibration control is generally used to reduce vibration level by the actuators based on measured signal. Dynamic properties of a structure can be easily modified by the active vibration control, so that the vibration level may be effectively reduced to the magnitude below the allowable limit over a wide frequency rangs. In this paper, an instantaneous optimal control algorithm including acceleration feedback is presented for the active vibration control of large structures considering facts that the acceleration response can be easily measured, but the displacement and velocity response are obtained by numerically integrating the measured acceleration response with some errors. The adverse effect of the time delay is overcomed by taking into account the dynamic characteristics of an actuator and filters in the design of controller. Performance test is carried out using a hydraulic active mass driver on a test structure$(L{\times}W{\times}H;=;1200mm{\times}800mm{\times}1600mm, about;500kg)$ supported by four columns under base excitations. It is confirmed that the vibration level of the test structure are reduced to about 1/6 near resonance.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.6
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• pp.31-37
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• 2002

This paper presents a new motion control strategy for singularity avoidance in 6 DOF articulated robot manipulators, based on a speed limiting algorithm for joint positions and velocities. For a given task, the robot is controlled so that the joints move with acceptable velocities and positions within the reachable range of each joint by considering the velocity limit. This paper aims at the development of a new efficient method to control robot motion near and at singularities. The proposed method has focused on generating the optimal joint trajectory for a Cartesian end-effector path within the speed limit of each joint by using the speed limit avoidance as well as the acceleration/deceleration scheme. The proposed method was verified using MATLAB-based simulations.

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.93-102
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• 2010

In this study, a smart sky-bridge composed of MR damper and FPS has been proposed and vibration control performance of a smart sky-bridge for the connected buildings was investigated. To this end, 10-story and 20-story building structures connected by a smart sky-bridge were selected as example structures and El Centro and Kobe earthquakes, which have near and far fault ground motion characteristics respectively, were used for time history analyses. In order to effectively control the smart sky-bridge, fuzzy logic controller was developed and multi-objective genetic algorithm was used to optimize fuzzy logic controllers. Based on optimization results, it has been seen that there is a trade-off between seismic responses of 10-story and 20-story buildings and a suite of Pareto optimal solutions of fuzzy logic controllers for seismic response control can be obtained by multi-objective genetic algorithm. It is shown from numerical study that seismic responses of adjacent buildings can be efficiently controlled by using a smart sky-bridge.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1272-1277
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• 2014

This article describes a path planning algorithm for fixed-wing UAVs when a real terrain should be considered. Nowadays, many UAVs are required to perform mission flights near given terrain for surveillance, reconnaissance, and infiltration, as well as flight altitude of many UAVs are relatively lower than typical manned aerial vehicles. Therefore, real terrain should be considered in path planning algorithms of fixed-wing UAVs. In this research, we have extended a spline-$RRT^*$ algorithm to three-dimensional planner. The spline-$RRT^*$ algorithm is a $RRT^*$ based algorithm, and it takes spline method to extend the tree structure over the workspace to generate smooth paths without any post-processing. Direction continuity of the resulting path is guaranteed via this spline technique, and it is essential factor for the paths of fixed-wing UAVs. The proposed algorithm confirm collision check during the tree structure extension, so that generated path is both geometrically and dynamically feasible in addition to direction continuity. To decrease degrees of freedom of a random configuration, we designed a function assigning directions to nodes of the graph. As a result, it increases the execution speed of the algorithm efficiently. In order to investigate the performance of the proposed planning algorithm, several simulations are performed under real terrain environment. Simulation results show that this proposed algorithm can be utilized effectively to path planning applications considering real terrain.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.442-445
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• 1997

We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.89-100
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• 2016

Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.44-47
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• 1996

Bang-bang control law provides the optimal solution for a minimum-time control problem, but ignores the intermediate path except for the initial and final points. In this paper, a near minimum-time suboptimal fuzzy logic controller is introduced that can control the intermediate path. A dynamic model for a system is established using the average dynamics method of linearization. System model is continuously updated over the control time periods. This makes it suitable for high speed or variable payload applications. Bang-bang control theory is modified and used to derive the preliminary control law. A fuzzy logic algorithm is then applied to adjust and find the best solution. The solution will provide the suboptimal minimum-time control law which can avoid obstacles in the workspace.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.303-308
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• 1992

In this study, we propose a shared storage system which is more efficient policy than MIS(Mixed Intermediate Storage) policy for relatively rare storage system and can be called CIS(Common Intermediate Storage) policy. Using this strategy, we develop a new completion time algorithm and apply it to two kinds of optimal or near optimal scheduling method; combinatorial search and simulated annealing method. We also extend this strategy to other storage policy, for example MIS policy, with PLC(Programmable Logic Controller) logic and on/off action of electronic valves. It thus can be accepted as a basic form of FMS(Flexible Manufacturing System) for operating various storage policies. Finally we suggest the interlocking block to compansate for the shortcoming of CIS policy, i.e, complication of operation and safety, resulting in a basic batch process automation mode.