• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.482-483
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• 2008

This paper compares particle swarm optimization techniques for PV allocation planning problem in power systems. PV allocation planning problem is formulated as a mixed-integer nonlinear problem. Five variants of PSO techniques are investigated for the applicability on the PV allocation problem. Namely, PSO with constant inertia weight approach (PSO-CIW), PSO with time varying inertia weight (PSO-TVIW), PSO with random inertia weight (PSO-RIW), PSO with constriction factor (PSO-CF) and PSO with time varying acceleration coefficients (PSO-TVAC).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.4
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• pp.203-209
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• 2023

Harmony search(HS) does not use the evaluation of individual harmony when referring to HM when constructing a new harmony, but particle swarm optimization(PSO), on the contrary, uses the evaluation value of individual particles and the evaluation value of the population to find a solution. However, in this study, we tried to improve the performance of the algorithm by finding and identifying similarities between HS and PSO and applying the particle improvement process of PSO to HS. To apply the PSO algorithm, the local best of individual particles and the global best of the swam are required. In this study, the process of HS improving the worst harmony in harmony memory(HM) was viewed as a process very similar to that of PSO. Therefore, the worst harmony of HM was regarded as the local best of a particle, and the best harmony was regarded as the global best of swam. In this way, the performance of the HS was improved by introducing the particle improvement process of the PSO into the HS harmony improvement process. The results of this study were confirmed by comparing examples of optimization values for various functions. As a result, it was found that the suggested HS-PSO was much better than the existing HS in terms of accuracy and consistency.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1777-1782
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• 2011

Brushless DC motors applied in many control systems because of the good respose characteristic and the easy control characteristic. The speed control of the BLDC motors is important in the systems. This paper has designed PSO-PID speed controller for the speed control of BLDC motors. The PSO algorithm optimized the parameters of the PID controller in the PSO-PID speed controller. The several methods obtained the optimal inertia weight of the PSO algorithm by comparison. The optimal inertia weight of the PSO algorithm optimized the PSO-PID speed controller for BLDC motors. This paper confirmed the performance of proposed PSO-PID speed controller through simulation results.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.559-570
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• 2008

This paper proposes an improved particle swarm optimization named PSO with Controllable Random Exploration Velocity (PSO-CREV) behaving an additional exploration behavior. Different from other improvements on PSO, the updating principle of PSO-CREV is constructed in terms of stochastic approximation diagram. Hence a stochastic velocity independent on cognitive and social components of PSO can be added to the updating principle, so that particles have strong exploration ability than those of conventional PSO. The conditions and main behaviors of PSO-CREV are described. Two properties in terms of "divergence before convergence" and "controllable exploration behavior" are presented, which promote the performance of PSO-CREV. An experimental method based on a complex test function is proposed by which the proper parameters of PSO-CREV used in practice are figured out, which guarantees the high exploration ability, as well as the convergence rate is concerned. The benchmarks and applications on FCRNN training verify the improvements brought by PSO-CREV.

• Korean Journal of Environmental Agriculture
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• v.20 no.3
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• pp.186-191
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• 2001

Recently, petroleum spray oil(PSO) has been used to control key pests in integrated pest management (IPM) of citrus and other orchards in Australia and USA. In order to clarify the influences of a newly developed PSO (D-C Tron $Plus^{(R)}$) on citrus leaves, 0.33% or 1.0% of PSO were sprayed to potted 4-year-old citrus trees under some kinds of condition, and then the changes of photosynthesis, transpiration, stomatal conductance and chlorophyll fluorescence(Fv/Fm) were determined. When sprayed with 1.0% PSO, the photosynthetic rate, transpiration and stomatal conductance of citrus leaves were decreased by 20%, and then recovered in 20 days after treatment (DAT), while there were little influences by the spray of 0.33% PSO. The value of Fv/Fm decreased more under the $34/24^{\circ}C$ temperature condition than that of under the $30/20^{\circ}C$ and $28/16^{\circ}C$ condition. The high temperature ($50^{\circ}C$ for 10 hours)-treated trees sprayed with PSO 1.0% or PSO 1.0% plus dithianon 1/2000 dilution showed not only the increase of rate in dropped leaf but also the reduced photosynthesis and Fv/Fm compared with $30/20^{\circ}C$ temperature-treated ones. From the results of this study, the spray of 1.0% PSO can inhibit the physiological activities in citrus leaf, particularly under high temperature condition after spray or the mixing-spray with a fungicide (dithianon WP, 75%).

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.32-41
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• 2011

This paper presents a new method of Fuzzy Particle Swarm Optimization (FPSO)-based Congestion Management (CM) by optimal rescheduling of active powers of generators. In the proposed method, generators are selected based on their sensitivity to the congested line for efficient utilization. The task of optimally rescheduling the active powers of the participating generators to reduce congestion in the transmission line is attempted by FPSO, Fitness Distance Ratio PSO (FDR-PSO), and conventional PSO. The FPSO and FDR-PSO algorithms are tested on the IEEE 30-bus and Practical Indian 75-bus systems, after which the results are compared with conventional PSO to determine the effectiveness of CM. Compared with FDR-PSO and PSO, FPSO can better perform the optimal rescheduling of generators to relieve congestion in the transmission line.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.12-19
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• 2016

In the case of hard problems to find solutions or complx combination problems, there are various optimization algorithms that are used to solve the problem. Among these optimization algorithms, the representative of the optimization algorithm created by imitating the behavior patterns of the organism is the PSO (Particle Swarm Optimization) algorithm. Since the PSO algorithm is easily implemented, and has superior performance, the PSO algorithm has been used in many fields, and has been applied. In particular, PSO-SAPARB (PSO with Swarm Arrangement, Parameter Adjustment and Reflective Boundary) algorithm is an advanced PSO algorithm created to complement the shortcomings of PSO algorithm. In this paper, this PSO-SAPARB algorithm was applied to the longitudinal controller design of a VTOL (Vertical Take-Off and Landing) aircraft that has the advantages of fixed-wing aircraft and rotorcraft among drones which has attracted attention in the field of UAVs. Also, through the introduction and performance of the Korean SBAS (Satellite Based Augmentation System) named KASS (Korea Augmentation Satellite System) which is being developed currently, this paper deals with the availability of algorithm such as the PSO-SAPARB.

• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.423-430
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• 2010

Particle swarm optimization (PSO) algorithm is designed to find a single global optimal point. However, the PSO needs to be modified in order to find multiple optimal points of a multimodal function. These modifications usually divide a swarm of particles into multiple subswarms; in turn, these subswarms try to find their own optimal point, resulting in multiple optimal points. In this work, we present a new PSO algorithm, called coupling PSO to find multiple optimal points of a multimodal function based on coupling particles. In the coupling PSO, each main particle may generate a new particle to form a couple, after which the couple searches its own optimal point using non-stop-moving PSO algorithm. We tested the suggested algorithm and other ones, such as clustering PSO and niche PSO, over three analytic functions. The coupling PSO algorithm was also applied to solve a significant benchmark problem, the TEAM workshop problem 22.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.660-666
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• 2011

In this paper, we proposed a Particle Swarm Optimization(PSO) to search the optimal link lengths for legged walking robot. In order to apply the PSO algorithm for the proposed, its walking robot kinematic analysis is needed. A crab robot based on four-bar linkage mechanism and Jansen mechanism is implemented in H/W. For the performance index of PSO, the stride length of the legged walking robot is defined, based on the propose kinematic analysis. Comparative simulation results present to illustrate the viability and effectiveness of the proposed method.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.331-332
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• 2010

PSO는 사회 심리학과 진화 계산에 영감을 얻어 Kenney와 Eberhart에 의해 처음 소개되었다. PSO는 다양한 분야의 연속문제들에 성공적으로 적용되어 왔으나, 시퀀셜 문제를 위한 PSO 연구는 거의 없었다. 본 논문에서는 일정 및 순서 문제에 PSO를 적옹하기 위해 난수 표현법을 사용한 PSO를 제안한다. 실험결과 제안한 알고리즘은 일정 및 순저 문제를 해결하기위한 좋은 가능성을 지녔음을 보여주었다.