• Title/Summary/Keyword: Genetic stability

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Research on Robust Stability Analysis and Worst Case Identification Methods for Parameters Uncertain Missiles

  • Hou, Zhenqian;Liang, Xiaogeng;Wang, Wenzheng
    • International Journal of Aeronautical and Space Sciences
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    • v.15 no.1
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    • pp.63-73
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    • 2014
  • For robust stability analysis of parameters uncertainty missiles, the traditional frequency domain method can only analyze each respective channel at several interval points within uncertain parameter space. Discontinuous calculation and couplings between channels will lead to inaccurate analysis results. A method based on the ${\nu}$-gap metric is proposed, which is able to comprehensively evaluate the robust stability of missiles with uncertain parameters; and then a genetic-simulated annealing hybrid optimization algorithm, which has global and local searching ability, is used to search for a parameters combination that leads to the worst stability within the space of uncertain parameters. Finally, the proposed method is used to analyze the robust stability of a re-entry missile with uncertain parameters; the results verify the feasibility and accuracy of the method.

Trajectory Parameter Optimization using Genetic Algorism (유전알고리즘을 이용한 워킹 궤적 파라미터의 최적화)

  • Son, In-Hye;Kim, Dong-Han;Park, Chong-Kug
    • Proceedings of the KIEE Conference
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    • 2008.04a
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    • pp.75-76
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    • 2008
  • In oder for the robot to walk with stability, trajectory generation method for the biped robot is important. In this paper proposed the genetic algorithm to optimize biped robot motion parameters. Because most of trajectory generation, the walking parameters determined arbitrarily. Formulating the constraints of the motion parameters, and the trajectory is derived by cubic spline function. Finally walking patterns are described through simulation studies. When the ZMP(zero moment point) and DSM(dynamic stability margin) are satisfied, the walking pattern is chosen.

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Sizing, shape and topology optimization of trusses with energy approach

  • Nguyena, Xuan-Hoang;Lee, Jaehong
    • Structural Engineering and Mechanics
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    • v.56 no.1
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    • pp.107-121
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    • 2015
  • The main objective of this research is to present the procedures of combining topology, shape & sizing optimization for truss structure by employing strain energy as objective function under the constraints of volume fractions which yield more general solution than that of total weight approach. Genetic Algorithm (GA) is used as searching engine for the convergence solution. A number of algorithms from previous research are used for evaluating the feasibility and stability of candidate to accelerate convergence and reduce the computational effort. It is followed by solving problem for topology & shape optimization and topology, shape & sizing optimization of truss structure to illustrate the feasibility of applying the objective function of strain energy throughout optimization stages.

Design of GA-Fuzzy Precompensator of TCSC-PSS for Enhancement of Power System Stability (전력계통 안정도 향상을 위한 TCSC 안정화 장치의 GA-퍼지 전 보상기 설계)

  • Wang Yong-Peel;Chung Mun-Kyu;Chung Hyeng-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.54 no.2
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    • pp.51-60
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    • 2005
  • In this paper, we design the GA-fuzzy precompensator of a Power System Stabilizer for Thyristor Controlled Series Capacitor(TCSC-PSS) for enhancement of power system stability. Here a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for TCSC-PSS. This scheme is easily implemented by adding a fuzzy precompensator to an existing TCSC-PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Nonlinear simulation results show that the proposed control technique is superior to conventional TCSC-PSS in dynamic responses over the wide range of operating conditions and in convinced robust and reliable in view of structure.

Design of GA-Fuzzy Precompensator for Enhancement of Pourer System Stability (전력시스템의 안정도 향상을 위한 GA-퍼지 전 보상기 설계)

  • Jeong, Hyeong-Hwan;Jeong, Mun-Gyu;Lee, Jeong-Pil
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.2
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    • pp.83-92
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    • 2002
  • In this paper, we design a GA-fuzzy precompensator for enhancement of power system stability. Here, a fuzzy prerompensator is designed as a fuzzy logic-based precompensation approach for Power System Stabilizer(PSS). This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

Real-Time Estimation of Multi TCSC Reference Quantity for Improvement of Transient Stability Energy Margin (과도안정도 에너지 마진 향상을 위한 다기의 TCSC 적정량 실시간 산정)

  • Kim, Su-Nam;Yu, Seok-Gu
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.10
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    • pp.454-463
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    • 2001
  • This paper presents a method for real-time estimation of TCSC reference quantity in order to enhance the power system transient stability energy margin using artificial neural network in multi-machine system. This paper has the three parts, the first part is to determine the lines to be installed by TCSC. The seconds is to estimate the energy margin using by ANN. To get the critical energy for training, we use the potential energy boundary surface(PEBS) method which is one of the transient energy function(TEF) method. And the last is to determine the TCSC reference quantity. In order to make training data for ANN in this step, we use genetic algorithm(GA). The proposed method is applied to 39-bus, 46-line. 10-machine model system to show its effectiveness.

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Design of TCSC-PSS using Genetic Algorithm for Enhancement of Power System Stability (전력계통의 안정도 향상을 위한 유전알고리즘을 이용한 TCSC 안정화장치 설계)

  • Chung, Mun-Kyu;Chung, Hyeong-Hwan;Hur, Dong-Ryol;Joo, Seok-Min;Chung, Dong-Il
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.227-229
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    • 2003
  • In this paper, we design a Power System Stabilizer for a Thyristor Controlled Series Capacitor(TCSC-PSS) for enhancement of power system stability. Here, PSS parameters are optimized using Genetic Algorithm(GA) in order to maintain optimal operation of TCSC. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

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Feedback linearization control of a nonlinear system using genetic algorithms and fuzzy logic system (유전 알고리듬과 퍼지논리 시스템을 이용한 비선형 시스템의 피드백 선형화 제어)

  • 최영길;김성현;심귀보;전홍태
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.3
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    • pp.46-54
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    • 1997
  • In this paper, we psropose the feedback linearization technique for a nonlinear system using genetic algorithms (GAs) and fuzzy logic system. The proposed control scheme approximates the nonlinear term of a nonlinear system using the fuzzy logic system and computes the control input for cancelling the nonlinear term. Then in the fuzzy logic system, the number and shape of membership function of the premise aprt will be tuned to minimize the control error boundary using GAs. And the parameters of the consequence of fuzzy rule will be tuned by the adaptive laws based on lyapunov stability theory in order to guarantee the closed loop stability of control system. The evolution of fuzzy logic system is processed during the on-line adaptive control. The effectiveness of proposed method will be demonstrated by computer simulation of simple nonlinear sytem.

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A GA-based Heuristic for the Interrelated Container Selection Loading Problems

  • Techanitisawad, Anulark;Tangwiwatwong, Paisitt
    • Industrial Engineering and Management Systems
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    • v.3 no.1
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    • pp.22-37
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    • 2004
  • An integrated heuristic approach based on genetic algorithms (GAs) is proposed for solving the container selection and loading problems. The GA for container selection solves a two-dimensional knapsack problem, determining a set of containers to minimize the transportation or shipment cost. The GA for container loading solves for the weighted coefficients in the evaluation functions that are applied in selecting loading positions and boxes to be loaded, so that the volume utilization is maximized. Several loading constraints such as box orientation, stack priority, stack stability, and container stability are also incorporated into the algorithm. In general, our computational results based on randomly generated data and problems from the literature suggest that the proposed heuristic provides a good solution in a reasonable amount of computational time.

Design of Robust GA-QFT Controller for Enhancement of Power System Stability (전력계통의 안정도 향상을 위한 강인한 GA-QFT 제어기 설계)

  • Chung, Hyeong-Hwan;Lee, Jeong-Phil;Hur, Dong-Ryol;Kim, Chang-Hyun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.4
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    • pp.197-207
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    • 2001
  • In this paper, design problem of QFT-PSS using Genetic Algorithm(GA) is investigated for power systems with parameter variation and disturbance uncertainties. A robust controller for uncertain power systems can be designed automatically such that the cost of feedback is minimized and all robust stability and performance specifications are satisfied. It is shown that the proposed design method not only automates loop shaping but also improves design quality and improves the quality with a reduced order controller. The robustness of the proposed controller has been investigated on a single machine infinite bus model. The results are shown that the proposed QFT-PSS using GA is more robust tan conventional PSS.

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