• ETRI Journal
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• 제35권6호
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• pp.1168-1171
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• 2013

We propose an improvement of particle swarm optimization (PSO) based on the stabilization of particle movement (PM). PSO uses a stochastic variable to avoid an unfortunate state in which every particle quickly settles into a unanimous, unchanging direction, which leads to overshoot around the optimum position, resulting in a slow convergence. This study shows that randomly located particles may converge at a fast speed and lower overshoot by using the proportional-integral-derivative approach, which is a widely used feedback control mechanism. A benchmark consisting of representative training datasets in the domains of function approximations and pattern recognitions is used to evaluate the performance of the proposed PSO. The final outcome confirms the improved performance of the PSO through facilitating the stabilization of PM.

• Structural Engineering and Mechanics
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• 제53권6호
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• pp.1127-1141
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• 2015

The optimum design of liquid column dampers in seismic vibration control considering system parameter uncertainty is usually performed by minimizing the unconditional response of a structure without any consideration to the variation of damper performance due to uncertainty. However, the system so designed may be sensitive to the variations of input system parameters due to uncertainty. The present study is concerned with robust design optimization (RDO) of liquid column vibration absorber (LCVA) considering random system parameters characterizing the primary structure and ground motion model. The RDO is obtained by minimizing the weighted sum of the mean value of the root mean square displacement of the primary structure as well as its standard deviation. A numerical study elucidates the importance of the RDO procedure for design of LCVA system by comparing the RDO results with the results obtained by the conventional stochastic structural optimization procedure and the unconditional response based optimization.

• Earthquakes and Structures
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• 제14권3호
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• pp.215-227
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• 2018

Supplemental passive control devices are widely considered as an important tool to mitigate the dynamic response of a building under seismic excitation. Nevertheless, a systematic method for strategically placing dampers in the buildings is not prescribed in building codes and guidelines. Many deterministic and stochastic methods have been proposed by previous researchers to investigate the optimum distribution of the viscous dampers in the steel frames. However, the seismic performances of the retrofitted buildings that are under large earthquake intensity levels or near collapse state have not been evaluated by any seismic research. Recent years, an increasing number of studies utilize genetic algorithms (GA) to explore the complex engineering optimization problems. GA interfaced with nonlinear response history (NRH) analysis is considered as one of the most powerful and popular stochastic methods to deal with the nonlinear optimization problem of damper distribution. In this paper, the effectiveness and the efficiency of GA on optimizing damper distribution are first evaluated by strong ground motions associated with the collapse failure. A practical optimization framework using GA and NRH analysis is proposed for optimizing the distribution of the fluid viscous dampers within the moment resisting frames (MRF) regarding the improvements of large drifts under intensive seismic context. Both a 10-storey and a 20-storey building are involved to explore higher mode effect. A far-fault and a near-fault earthquake environment are also considered for the frames under different seismic intensity levels. To evaluate the improvements obtained from the GA optimization regarding the collapse performance of the buildings, Incremental Dynamic Analysis (IDA) is conducted and comparisons are made between the GA damper distribution and stiffness proportional damping distribution on the collapse probability of the retrofitted frames.

• Structural Engineering and Mechanics
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• 제36권5호
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• pp.561-573
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• 2010

The potential of the liquid column vibration absorber (LCVA) as a seismic vibration control device for structures has been explored in this paper. In this work, the structure has been modeled as a linear, viscously damped single-degree-of-freedom (SDOF) system. The governing differential equations of motion for the damper liquid and for the coupled structure-LCVA system have been derived from dynamic equilibrium. The nonlinear orifice damping in the LCVA has been linearized by a stochastic equivalent linearization technique. A transfer function formulation for the structure-LCVA system has been presented. The design parameters of the LCVA have been identified and by applying the transfer function formulation the optimum combination of these parameters has been determined to obtain the most efficient control performance of the LCVA in terms of the reduction in the root-mean-square (r.m.s.) displacement response of the structure. The study has been carried out for an example structure subjected to base input characterized by a white noise power spectral density function (PSDF). The sensitivity of the performance of the LCVA to the coefficient of head loss and to the tuning ratio have also been examined and compared with that of the liquid column damper (LCD). Finally, a simulation study has been carried out with a recorded accelerogram, to demonstrate the effectiveness of the LCVA.

• 융합신호처리학회논문지
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• 제13권4호
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• pp.207-210
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• 2012

유전 알고리즘은 확률에 기반한 매우 효과적인 최적화 기법이지만 지역해로의 조기수렴과 전역해로의 수렴 속도가 느리다는 단점이 있다. 본 논문에서는 이러한 단점을 보완하기 위해 적응 분할법에 기반한 유전 알고리즘을 제안하였다. 유전 알고리즘이 전역해를 효과적으로 찾도록 하는 적응 분할법은 최적화의 복잡도를 줄이기 위해 탐색공간을 적응적으로 분할한다. 이러한 적응 분할법은 탐색공간의 복잡도가 증가할수록 더 효과적이다. 제안된 방법을 테스트 함수의 최적화 및 도립진자 제어를 위한 퍼지 제어기 설계 최적화에 적용하여 그 유효성을 보였다.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.643-653
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• 2017

The paper presents controller optimization algorithm for a 12-pulse voltage source converter (VSC) based high voltage direct current (HVDC) system. To get an optimum algorithm, three methods namely conventional-Zeigler-Nichols, linear-golden section search (GSS) and stochastic-particle swarm optimization (PSO) are applied to control of 12 pulse VSC based HVDC system and simulation results are presented to show the best among the three. The performance results are obtained under various dynamic conditions such as load perturbation, non-linear load condition, and voltage sag, tapped load fault at points-of-common coupling (PCC) and single-line-to ground (SLG) fault at input AC mains. The conventional GSS and PSO algorithm are modified to enhance their performances under dynamic conditions. The results of this study show that modified particle swarm optimization provides the best results in terms of quick response to the dynamic conditions as compared to other optimization methods.

• 대한기계학회논문집A
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• 제28권10호
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• pp.1558-1565
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• 2004

It is important to determine supporting locations for structural stability when a structure is loaded with non-uniform load or supporting locations as well as the number of the supporting structures are restricted by the problem of space. Moreover, the supporting location optimization of complex structure in real world is frequently faced with discontinuous design space. Therefore, the traditional optimization methods based on derivative are not suitable Whereas, Genetic Algorithm (CA) based on stochastic search technique is a very robust and general method. The KSTAR in-vessel control coil installed in vacuum vessel is loaded with non- uniform electro-magnetic load and supporting locations are restricted by the problem of space. This paper shows the supporting location optimization for structural stability of the in-vessel control coil. Optimization has been performed by means of a developed program. It consists of a Finite Element Analysis interfaced with a Genetic Algorithm. In addition, this paper presents an algorithm to find an optimum solution in discontinuous space using continuous design variables.