• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1796-1803
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• 2013

In this paper, a novel particle swarm optimization method based on IE3D is used to design a mobile communication microstrip patch antenna. The aim of the paper is to design and fabricate an inset fed rectangular microstrip antenna and study the effect of antenna dimensions length (L), width (W) and substrate parameters relative dielectric constant (${\varepsilon}r$), substrate thickness on radiation parameters of band width. PSO algorism was applied to IE3D, low resistance against, band width and advantage, were improved.

• Journal of Power Electronics
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• v.19 no.4
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• pp.835-845
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• 2019

This paper presents a robust-optimal control strategy to improve the output-voltage error-tracking and control capability of a DC-DC boost converter. The proposed strategy employs an optimized Fractional-order Proportional-Integral (FoPI) controller that serves to eliminate oscillations, overshoots, undershoots and steady-state fluctuations. In order to significantly improve the error convergence-rate during a transient response, the FoPI controller is augmented with a pre-stage nonlinear error-modulator. The modulator combines the variations in the error and error-derivative via the signed-distance method. Then it feeds the aggregated-signal to a smooth sigmoidal control surface constituting an optimized hyperbolic secant function. The error-derivative is evaluated by measuring the output-capacitor current in order to compensate the hysteresis effect rendered by the parasitic impedances. The resulting modulated-signal is fed to the FoPI controller. The fixed controller parameters are meta-heuristically selected via a Particle-Swarm-Optimization (PSO) algorithm. The proposed control scheme exhibits rapid transits with improved damping in its response which aids in efficiently rejecting external disturbances such as load-transients and input-fluctuations. The superior robustness and time-optimality of the proposed control strategy is validated via experimental results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.617-635
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• 2020

The purpose of this study is to discuss how to improve the maneuverability of lifting and diving for underwater vehicle's vertical motion. Therefore, to solve these problems, applied the 3-D numerical simulation, Taguchi's Design of Experiment (DOE), and intelligent parameter design methods, etc. We planned four steps as follows: firstly, we applied the 2-D flow simulation with NACA series, and then through the Taguchi's dynamic method to analyze the sensitivity (β). Secondly, take the data of pitching torque and total resistance from the Taguchi orthogonal array (L9), the ignal-to-noise ratio (SNR), and analysis each factorial contribution by ANOVA. Thirdly, used Radial Basis Function Network (RBFN) method to train the non-linear meta-modeling and found out the best factorial combination by Particle Swarm Optimization (PSO) and Weighted Percentage Reduction of Quality Loss (WPRQL). Finally, the application of the above methods gives the global optimum for multi-quality characteristics and the robust design configuration, including L/D is 9.4:1, the foreplane on the hull (Bow-2), and position of the sail is 0.25 Ls from the bow. The result shows that the total quality is improved by 86.03% in comparison with the original design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.735-748
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• 2014

The fault-tolerance routing problem is one of the most important issues in the application of the Internet of Things, and has been attracting growing research interests. In order to maintain the communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which alternate paths are created once the previous routing is broken. Then, we propose an improved efficient and intelligent fault-tolerance algorithm (IEIFTA) to provide the fast routing recovery and reconstruct the network topology for path failure in the Internet of Things. In the IEIFTA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by the immune mechanism, which can improve the ability of global search and improve the converging rate of the algorithm. The simulation results indicate that the IEIFTA-based fault-tolerance algorithm outperforms the EARQ algorithm and the SPSOA algorithm due to its ability of fast routing recovery mechanism and prolonging the lifetime of the Internet of Things.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1178-1191
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• 2014

The fault-tolerance routing problem is one of the most important issues in the application of the Internet of Things, and has been attracting growing research interests. In order to maintain the communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which alternate paths are created once the previous routing is broken. Then, we propose an improved efficient and intelligent fault-tolerance algorithm (IEIFTA) to provide the fast routing recovery and reconstruct the network topology for path failure in the Internet of Things. In the IEIFTA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by the immune mechanism, which can improve the ability of global search and improve the converging rate of the algorithm. The simulation results indicate that the IEIFTA-based fault-tolerance algorithm outperforms the EARQ algorithm and the SPSOA algorithm due to its ability of fast routing recovery mechanism and prolonging the lifetime of the Internet of Things.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.527-531
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• 2012

In this paper, a novel DPSO-QI (Distributed PSO with quantum-infusion mechanism) algorithm improving one of the fatal defect, the so-called premature convergence, that degrades the performance of the conventional PSO algorithms is proposed. The proposed scheme has the following two distinguished features. First, a concept of neighborhood of each particle is introduced, which divides the whole swarm into several small groups with an appropriate size. Such a strategy restricts the information exchange between particles to be done only in each small group. It thus results in the improvement of particles' diversity and further minimization of a probability of occurring the premature convergence phenomena. Second, a quantum-infusion (QI) mechanism based on the quantum mechanics is introduced to generate a meaningful offspring in each small group. This offspring in our PSO mechanism improves the ability to explore a wider area precisely compared to the conventional one, so that the degree of precision of the algorithm is improved. Finally, some numerical results are compared with those of the conventional researches, which clearly demonstrates the effectiveness and reliability of the proposed DPSO-QI algorithm.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.42-51
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• 2017

Due to the high degree of mechanization and the good environmental benefits, the prefabricated buildings are being promoted in China. The construction site layout of the prefabricated buildings has important influence on its safety benefit. However, few scholars have studied the safety problem on it. Firstly, in order to give a follow-up study foreshadowing the characteristics of prefabricated buildings are analyzed, the research assumptions are given and three types of safety buffers are established. And then a mult-objective model for the prefabricated buildings site layout is presented: taking into account the limits of noise, the coverage of the tower crane and the possibility of exceeding boundaries and overlapping, the constraints are and designed established respectively; Based on the improved System Layout Planning (SLP) method, the efficiency\cost\safety interaction matrices among the facilities are also founded for objective function. For the sake of convenience, a hypothetical facility layout case of the prefabricated building is used, the optimal solution of that is obtained in MATLAB with particle swarm algorithm (PSO), which proves the effectiveness of the model presented in this paper.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2319-2323
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• 2010

The existing contact-type bearings using rolling or sliding require continuous maintenance due to abrasion caused by friction and are not suitable for high-speed rotation and slimming. A magnetic bearing without contact can overcome such problems but the performance depends on the allocation of magnets and the structure of bearings. This paper proposes a method designing parameters of a passive magnetic bearing to improve levitation force. The proposed method employs Halbach array as the allocation of magnets, uses particle swam optimization to determine the structure of bearings. The numerical experiment shows that the levitation force is improved by the proposed method compared with the existing one using finite element analysis.

• Journal of IKEEE
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• v.22 no.3
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• pp.793-799
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• 2018

An improved design of Ultra Wide Band(UWB) Bow-Tie antenna, which can control an enhanced wide stop-band, is presented. The mutually coupled slot-pair improves and controls the rejection band. The UWB antenna is composed of an electromagnetically coupled Bow-Tie patch and a parasitic ground patch, whose working frequency is extended to full UWB range in this work. By adding slot-pairs on the main patch and optimizing, they can give any requested wide rejection bands and sharp skirt characteristics, as is often required for UWB antennas and multi-band antennas. All the parameters are precisely calculated by an adequate optimization method. The Particle Swarm Optimization(PSO) technique is appropriately adopted. The proposed design and method is proved to give and control the sharp-skirt wide stop-band to UWB Bow-Tie antennas.