• Title/Summary/Keyword: optimization modeling

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Fractional Order Modeling and Control of Twin Rotor Aero Dynamical System using Nelder Mead Optimization

  • Ijaz, Salman;Hamayun, Mirza Tariq;Yan, Lin;Mumtaz, Muhammad Faisal
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1863-1871
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    • 2016
  • This paper presents an application of fractional order controller for the control of multi input multi output twin rotor aerodynamic system. Dynamics of the considered system are highly nonlinear and there exists a significant cross-coupling between the horizontal and vertical axes (pitch & yaw). In this paper, a fractional order model of twin rotor aerodynamic system is identified using input output data from nonlinear system. Based upon identified fractional order model, a fractional order PID controller is designed to control the angular position of level bar of twin rotor aerodynamic system. The parameters of controller are tuned using Nelder-Mead optimization and compared with particle swarm optimization techniques. Simulation results on the nonlinear model show a significant improvement in the performance of fractional order PID controller as compared to a classical PID controller.

Optimal Trajectory Modeling of Humanoid Robot for Argentina Tango Walking

  • Ahn, Doo-Sung
    • Journal of Power System Engineering
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    • v.21 no.5
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    • pp.41-47
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    • 2017
  • To implement Argentina tango dancer-like walking of the humanoid robot, a new trajectory generation scheme based on particle swarm optimization of the blending polynomial is presented. Firstly, the characteristics of Argentina tango walking are derived from observation of tango dance. Secondly, these are reflected in walking pose conditions and cost functions of particle swarm optimization to determine the coefficients of blending polynomial. For the stability of biped walking, zero moment point and reference trajectory of swing foot are also included in cost function. Thirdly, after tango walking cycle is divided into 3 stages with 2 postures, optimal trajectories of ankles, knees and hip of lower body, which include 6 sagittal and 4 coronal angles, are derived in consequence of optimization. Finally, the feasibility of the proposed scheme is validated by simulating biped walking of humanoid robot with derived trajectories under the 3D Simscape environment.

Evolutionary Network Optimization: Hybrid Genetic Algorithms Approach

  • Gen, Mitsuo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.195-204
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    • 2003
  • Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

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Optimization of a Train Suspension using Kriging Meta-model (크리깅 메타모델에 의한 철도차량 현수장치 최적설계)

  • Lee, Kwang-Ki;Lee, Tae-Hee;Park, Chan-Kyoung
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.339-344
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    • 2001
  • In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

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Evaluation for Charging effects of Plug-in Electrical Vehicles in Power System considering Optimal Charging scenarios (전기자동차의 충전부하특성 모델링 및 충전 시나리오에 따른 계통평가)

  • Moon, Sang-Keun;Kim, Sung-Yul;Kin, Jin-O
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.298-299
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    • 2011
  • The impacts of EV charging demands on power system such as increased peak demands may be developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes are proposed to determine optimal demand distribution portions so that charging costs and demands can be managed optimally. There are two optimization methods which have different effects on the outcome. These focus either on the Electric vehicle customer side (cost optimization) or the System Operator side (Load-weighted optimization).

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Development of Optimization Methodology for Laser Welding Process Automation Using Neural Network Model and Objective Function (레이저 용접공정의 자동화를 위한 신경망 모델과 목적함수를 이용한 최적화 기법 개발)

  • Park, Young-Whan
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.15 no.5
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    • pp.123-130
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    • 2006
  • In manufacturing, process automation and parameter optimization are required in order to improve productivity. Especially in welding process, productivity and weldablity should be considered to determine the process parameter. In this paper, optimization methodology was proposed to determine the welding conditions using the objective function in terms of productivity and weldablity. In order to conduct this, welding experiments were carried out. Tensile test was performed to evaluate the weldability. Neural network model to estimate tensile strength using the laser power, welding speed, and wire feed rate was developed. Objective function was defined using the normalized tensile strength which represented the weldablilty and welding speed and wire feed rate which represented the productivity. The optimal welding parameters which maximized the objective function were determined.

Optimal design of an electro-pneumatic automatic transfer system

  • Um, Taijoon
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.71-75
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    • 1994
  • This paper presents a method of optimal design of an automatic transfer system which is controlled by the electro-pneumatic servo scheme. The electro-pneumatic automatic transfer system can move parts to desired points or displace defective parts. The dynamic performance of the system can be examined by observing the behavior of the output. The output of the servo control system is the motion of the cylinder, pneumatic actuator. The dynamic performance of the cylinder is governed by the parameters of the components of the entire system. The optimal design can be accomplished by selecting of the parameters such that the desired dynamic performance of the cylinder is obtained. The optimal set of parameters might be obtained through the repeated simulations. Repeated simulations, however, is not effective to determine the optimal set of parameters since the set of parameters is large. This paper presents modeling, application of an optimization method, and the numerical results. The optimization algorithm utilizes the concept of the conjugate gradient method. The results show that the suggested optimization scheme can render faster convergence of iteration compared to other method based on an algebraic optimization method and can reduce the design efforts.

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Design Optimization of a Printed Circuit Heat Exchanger Using Surrogate Models (대리모델들을 이용한 인쇄형 열교환기의 최적설계)

  • Lee, Sang-Moon;Kim, Kwang-Yong
    • The KSFM Journal of Fluid Machinery
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    • v.14 no.5
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    • pp.55-62
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    • 2011
  • Shape optimization of a Printed circuit heat exchanger (PCHE) has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (3-D RANS) analysis and surrogate modeling techniques. The objective function is defined as a linear combination of effectiveness of the PCHE term and pressure drop in the cold channels of the PCHE. The cold channel angle and the ellipse aspect ratio of the cold channel are used as design variables for the optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results of three types of surrogate model are compared each other. The results of the optimizations indicate improved performance in friction loss but low performance in effectiveness than the reference shape.

DESIGN OPTIMIZATION OF UPPER PLENUM OF PBMR USING RESPONSE SURFACE APPROXIMATION (반응면기법을 이용한 PBMR 기체냉각형 고온가스로 상층부의 최적설계)

  • Lee, S.M.;Kim, K.Y.
    • 한국전산유체공학회:학술대회논문집
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    • 2010.05a
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    • pp.187-194
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    • 2010
  • Shape optimization of an upper plenum of PBMR type gas cooled nuclear reactor has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. The objective function is defined as a linear combination of uniformity of flow distribution in the core and pressure drop in the upper plenum and the core. The ratio of thickness of slot to diameter of rising channels, ratio of height of upper plenum to diameter of rising channels, and ratio of eight of the slot at inlet to outlet, are used as design variables for optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results show that the optimum shape represent remarkably improved performance in flow uniformity and friction loss than the reference shape.

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DESIGN OPTIMIZATION OF UPPER PLENUM OF PBMR USING RESPONSE SURFACE APPROXIMATION (반응면기법을 이용한 PBMR 기체냉각형 고온가스로 상층부의 최적설계)

  • Lee, S.M.;Kim, K.Y.
    • Journal of computational fluids engineering
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    • v.15 no.3
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    • pp.16-23
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    • 2010
  • Shape optimization of an upper plenum of a PBMR type gas cooled nuclear reactor has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. The objective function is defined as a linear combination of uniformity of flow distribution in the core and pressure drop in the upper plenum and the core. The ratio of thickness of slot to diameter of rising channels, ratio of height of upper plenum to diameter of rising channels, and ratio of height of the slot at inlet to outlet, are used as design variables for optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results show that the optimum shape represent remarkably improved performance in flow uniformity and friction loss than the reference shape.