• 제목/요약/키워드: Modified genetic algorithm

검색결과 203건 처리시간 0.025초

초고압 직류송전 시스템의 전력 동요억제를 위한 정지형 무효전력 보상기에 MGA-PI 보조제어기 설계 (A Design of MGA-Pl Supplementary Controller in SVC for Power Oscillation Damping of HVDC Transmission System)

  • 오태규;정형환;허동열;이정필
    • 대한전기학회논문지:전력기술부문A
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    • 제51권7호
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    • pp.317-326
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    • 2002
  • In this paper, a methodology for optimal PI supplementary controller using the modified genetic algorithm has been proposed to the oscillation damping in HDVC transmission system. These study processes are summarized as the formulation for load flow calculation in HVDC transmission system with SVC, the investigations on the basic control in HVDC system, the mathematical modeling for dynamic characteristics analyses, and the optimal design of MGA based PI controller generation the supplementary control signal of SVC. Its properties were verified through a series of computer simulations including dynamic stability. It means that the application of MGA-PI controller in HVDC transmission system can contribute the propriety to the improvement of the stability in HVDC transmission system and the design of MGA-OI controller has been proved indispensible when applied to HVDC transmission system.

Seismic behavior enhancement of frame structure considering parameter sensitivity of self-centering braces

  • Xu, Longhe;Xie, Xingsi;Yan, Xintong;Li, Zhongxian
    • Structural Engineering and Mechanics
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    • 제71권1호
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    • pp.45-56
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    • 2019
  • A modified mechanical model of pre-pressed spring self-centering energy dissipation (PS-SCED) brace is proposed, and the hysteresis band is distinguished by the indication of relevant state variables. The MDOF frame system equipped with the braces is formulated in an incremental form of linear acceleration method. A multi-objective genetic algorithm (GA) based brace parameter optimization method is developed to obtain an optimal solution from the primary design scheme. Parameter sensitivities derived by the direct differentiation method are used to modify the change rate of parameters in the GA operator. A case study is conducted on a steel braced frame to illustrate the effect of brace parameters on node displacements, and validate the feasibility of the modified mechanical model. The optimization results and computational process information are compared among three cases of different strategies of parameter change as well. The accuracy is also verified by the calculation results of finite element model. This work can help the applications of PS-SCED brace optimization related to parameter sensitivity, and fulfill the systematic design procedure of PS-SCED brace-structure system with completed and prospective consequences.

Test Set Generation for Pairwise Testing Using Genetic Algorithms

  • Sabharwal, Sangeeta;Aggarwal, Manuj
    • Journal of Information Processing Systems
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    • 제13권5호
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    • pp.1089-1102
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    • 2017
  • In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

Optimized AI controller for reinforced concrete frame structures under earthquake excitation

  • Chen, Tim;Crosbie, Robert C.;Anandkumarb, Azita;Melville, Charles;Chan, Jcy
    • Advances in concrete construction
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    • 제11권1호
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    • pp.1-9
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    • 2021
  • This article discusses the issue of optimizing controller design issues, in which the artificial intelligence (AI) evolutionary bat (EB) optimization algorithm is combined with the fuzzy controller in the practical application of the building. The controller of the system design includes different sub-parts such as system initial condition parameters, EB optimal algorithm, fuzzy controller, stability analysis and sensor actuator. The advantage of the design is that for continuous systems with polytypic uncertainties, the integrated H2/H∞ robust output strategy with modified criterion is derived by asymptotically adjusting design parameters. Numerical verification of the time domain and the frequency domain shows that the novel system design provides precise prediction and control of the structural displacement response, which is necessary for the active control structure in the fuzzy model. Due to genetic algorithm (GA), we use a hierarchical conditions of the Hurwitz matrix test technique and the limits of average performance, Hierarchical Fitness Function Structure (HFFS). The dynamic fuzzy controller proposed in this paper is used to find the optimal control force required for active nonlinear control of building structures. This method has achieved successful results in closed system design from the example.

퍼지 균등화와 언어적인 Hedge를 이용한 GA 기반 퍼지 모델링 (GA based Fuzzy Modeling using Fuzzy Equalization and Linguistic Hedge)

  • 김승석;곽근창;유정웅;전명근
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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    • pp.217-220
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    • 2001
  • The fuzzy equalization method does not require the usual learning step for generating fuzzy rules. However it is heavily depend on the given input-output data set. So, we adapt an hierarchical scheme which sequentially optimizes the fuzzy inference system. Here, the parameters of fuzzy membership functions obtained from the fuzzy equalization are optimized by the genetic algorithm, and then they are also modified to increase the performance index using the linguistic hedge. Finally, we applied it to the Rice taste data and got better results than previous ones.

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배전계통 사고복구 문제에 갠선된 유전 알고리즘 적용 (An Application of Enhanced Genetic Algorithm to solve the Distribution System Restoration Problem)

  • 이정관;문경준;황기현;서정일;이화석;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 C
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    • pp.1123-1125
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    • 1999
  • This paper proposes an optimization technique using Genetic Algorithm(GA) for service restoration in the distribution system. Restoration planning problem can be treated as a combinatorial optimization problem. So GA is appropriate to solve the service restoration problem in the distribution network. But searching capabilities of the GA can be enhanced by developing relevant repairing operation and modifying GA operations. In this paper, we aimed at finding appropriate open sectionalizing switch position for the restoration of distribution networks after disturbances using enhanced GA with repairing operation and modified mutation. Simulation results show that proposed method found the open sectionalizing switches with less out of service area and minimize transmission line losses and voltage drop.

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Optimal Shape Design of Magnetic Actuators for Magnetic and Dynamic Characteristic Improvement

  • Yoo, Jeong-Hoon;Jung, Jae-Yeob;Hong, Hyeok-Soo
    • Journal of Magnetics
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    • 제16권3호
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    • pp.268-270
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    • 2011
  • This study introduces a new topology optimization scheme combing the genetic algorithm (GA) with the on/off sensitivity method for the magnetic actuator core and the armature design. The design process intended to maximize the first eigen-frequency of the armature part and the magnetic actuating force acting on the armature simultaneously. GA based optimal design was carried out to obtain the initial structure and the modified on/off sensitivity method was succeeded to accelerate the design process. Final results show tens of percent improvement in actuating force as well as the first eigen-frequency of the armature.

Evolutionary Design of a Fuzzy Logic Controller for Multi-Agent Systems

  • Jeong, Il-Kwon;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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    • pp.507-512
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    • 1998
  • It is an interesting area in the field of artificial intelligence to and an analytic model of cooperative structure for multi-agent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent co-operative behavior: A modified genetic algorithm was applied to automating the discovery of a fuzzy logic controller jot multi-agents playing a pursuit game. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to and the fuzzy logic controller seems to be promising.

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혼합 곡선 근사법을 이용한 선형 표현 (Hull Form Representation using a Hybrid Curve Approximation)

  • 김현철;이경선;김수영
    • 대한조선학회논문집
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    • 제35권4호
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    • pp.118-125
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    • 1998
  • 본 연구는 B-spline 근사법과 유전자 알고리즘을 이용하여 기하학적 경계 조건-양끝점의 위치 벡터 및 접선 벡터-을 만족하는 혼합 곡선 근사법에 의한 선형 표현을 내용으로 한다. B-spline 근사법을 이용하여 선형을 표현하고, 이들 곡선을 제어하는 조정점들이 기하학적 경계조건을 만족하도록 유전자 알고리즘으로 조정한다. 이 방법은 선형 생성시 순정 작업을 동시에 수행하므로 효율적인 선형 설계를 가능하게 한다.

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IMM Method Using Kalman Filter with Fuzzy Gain

  • 노선영;주영훈;박진배
    • 한국지능시스템학회논문지
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    • 제16권2호
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    • pp.234-239
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    • 2006
  • In this paper, we propose an interacting multiple model (IMM) method using intelligent tracking filter with fuzzy gain to reduce tracking errors for maneuvering targets. In the proposed filter, the unknown acceleration input for each sub-model is determined by mismatches between the modelled target dynamics and the actual target dynamics. After a acceleration input is detected, the state estimates for each sub-filter are modified. To modify the accurate estimation, we propose the fuzzy gain based on the relation between the filter residual and its variation. To optimize each fuzzy system, we utilize the genetic algorithm (GA). The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model(AIMM) method and input estimation (IE) method through computer simulations.