• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.541-547
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• 1992

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three-dimensional adaptive tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track update illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver detector. A detailed simulation is conducted to test the validity of our tracking algorithm for encounter geometries under various conditions of maneuver.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.795-803
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• 2015

Autoreclosure provides a means of improving power transmitting ability and system stability. Conventional reclosure adopts the fixed dead time interval strategy, where the reclosure is activated after a time delay to restore the system to normal as quickly as possible without regard to the system conditions. However, these simple techniques cannot provide optimal operating performance. This paper presents an adaptive autoreclosure algorithm including variable dead time, optimal reclosure, phase-by-phase reclosure and emergency extended equal-area criterion (EEEAC) algorithm in order to improve system stability. The reclosure algorithm performs the operations that are attuned to the power system conditions. The proposed adaptive reclosure algorithm is verified and tested using ATP/EMTP MODELS, and the simulation results show that the system oscillations are reduced and the transient stability is enhanced by employing the proposed adaptive reclosure algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.185-190
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• 2002

In distributed autonomous robotic systems (DARS), each robot must behave by itself according to its states ad environments, and if necessary, must cooperate with other robots in order to carry out their given tasks. Its most significant merit is that they determine their behavior independently, and cooperate with other robots in order to perform the given tasks. Especially, in DARS, it is essential for each robot to have evolution ability in order to increase the performance of system. In this paper, a schema co-evolutionary algorithm is proposed for the evolution of collective autonomous mobile robots. Each robot exchanges the information, chromosome used in this algorithm, through communication with other robots. Each robot diffuses its chromosome to two or more robots, receives other robot's chromosome and creates new species. Therefore if one robot receives another robot's chromosome, the robot creates new chromosome. We verify the effectiveness of the proposed algorithm by applying it to cooperative search problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.475-490
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• 2010

Cognitive Radio is an advanced enabling technology for the efficient utilization of vacant spectrum due to its ability to sense the spectrum environment. It is important to determine accurate spectrum utilization of the primary system in a cognitive radio environment. In order to define the spectrum utilization state, many CR systems use what is known as the quiet period (QP) method. However, even when using a QP, interference can occur. This causes reduced system throughput and contrary to the basic condition of cognitive radio. In order to reduce the interference time, a frequency-hopping algorithm is proposed here. Additionally, to complement the loss of throughput in the FH, a HMM-based channel prediction algorithm and a channel allocation algorithm is proposed. Simulations were conducted while varying several parameters. The findings show that the proposed algorithm outperforms conventional channel allocation algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1079-1083
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• 2014

In this paper, a new zone radius determination algorithm is proposed for a nature-inspired routing protocol that emulates the foraging behavior of bees based on their ability to find an optimal route from nectar sites. Instead of changing the radius of nodes one-hop by one-hop, the proposed algorithm alters the radius of nodes as gaps of another radius and adapt quickly to network conditions. The simulation results show that the proposed algorithm has higher efficiency compared with existing studies in an aspect of computational complexity and end-to-end delay.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.1979-1985
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• 2016

A protection algorithm using a voltage-controlled overcurrent element for a looped collection circuit in a wind farm is suggested in this paper. Because the proposed algorithm uses voltage relaying signals as well as current relaying signals, any fault in the looped collection circuit can be cleared by voltage-controlled overcurrent relays located at the two adjacent relaying points, the nearest place in each direction from the fault point. The algorithm can also distinguish the external faults which occur at the outside of a wind farm from the internal faults. It means that the proposed algorithm can provide the proper ability of protection coordination to the relays in the looped collection circuits of a large wind farm. The performance of the proposed algorithm is verified under various fault conditions using PSCAD/EMTDC simulations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.12
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• pp.698-704
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• 2003

Autoreclosure provides a mean of improving power transmitting ability and system stability. The conventional reclosure adopts the fixed dead time interval strategy, that is, the reclosure is activated after a time delay to restore the system to normal as quickly as possible without regard to the system conditions, however, these simple techniques cannot give the optimal operating performance. For this reason, various adaptive reclosure algorithms have been proposed recently, This paper presents an adaptive autoreclosure algorithm including the variable dead time, optimal reclosure, sequential reclosure and emergency extended equal-area criterion (EEAC) algorithm in order to improve the system stability. The reclosure algorithm performs out the operations that are attuned to the power system conditions. The proposed adaptive reclosure algorithm is verified and tested by using EMTP MODELS, and the simulation results show that the system oscillations are reduced and the transient stability is enhanced by employing the proposed adaptive reclosure algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.547-554
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• 2007

This thesis presents a kind of active noise control(ANC) algorithm for reducing noise due to engine inside a car. The proposed control algorithm is, by using WP(Wavelet Packet), a one improving the instability due to delay of noise transmission and the lack of response ability for the rapid change of noise, which are defects of the existing FXLMS(Filtered-X Least Mean Square) algorithm. The chief character of this system is a thing that faster operation than the FXLMS is implemented by inserting WP in the secondary path. In other words, WP implements parallel operation. Then, the weights of filter in the adaptive algorithm will be updated faster. In addition, because WP have so excellent a resolution, they can process very minute noise. The efficiency of this control algorithm will be demonstrated in the matlab simulation and in the actual experiments by using a Labview program and a car.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.71-78
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• 1997

In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

• Structural Engineering and Mechanics
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• v.36 no.5
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• pp.529-544
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• 2010

Nonlinear equations of structures are generally solved numerically by the iterative solution of linear equations. However, this iterative procedure diverges when the tangent stiffness is ill-conditioned which occurs near limit points. In other words, a major challenge with simple iterative methods is failure caused by a singular or near singular Jacobian matrix. In this paper, using the Newton-Raphson algorithm based on Davidenko's equations, the iterations can traverse the limit point without difficulty. It is argued that the propose algorithm may be both more computationally efficient and more robust compared to the other algorithm when tracing path through severe nonlinearities such as those associated with structural collapse. Two frames are analyzed using the proposed algorithm and the results are compared with the previous methods. The ability of the proposed method, particularly for tracing the limit points, is demonstrated by those numerical examples.