• Title/Summary/Keyword: Q-optimization

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Design of Disturbance Observer Based on Structural Analysis (구조적 분석에 기초한 외란관측기의 설계)

  • 김봉근
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.3
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    • pp.225-231
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    • 2004
  • Disturbance observer (DOB) has been studied extensively and applied to many motion control fields during the last decades, but relatively few studies have been devoted to the development of analytic, systematic design methods for DOB itself, This paper thus aims to provide an analytic, systematic design method for DOB. To do this, DOB is structurally analyzed and the generalized disturbance compensation framework named robust internal-loop compensator (RIC) is introduced. Through this, the inherent equivalence between DOB and RIC is found, and the mixed sensitivity optimization problem of DOB is solved. Q-filter design is completely separated from the mixed sensitivity optimization problems of DOB although the proposed method has implicit .elation with Q-filter. Also, although the Q-fille. is separately designed with sensitivity function, the proposed DOB framework has the exactly same characteristic as the original DOB.

ON COMPLEXITY ANALYSIS OF THE PRIMAL-DUAL INTERIOR-POINT METHOD FOR SECOND-ORDER CONE OPTIMIZATION PROBLEM

  • Choi, Bo-Kyung;Lee, Gue-Myung
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.14 no.2
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    • pp.93-111
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    • 2010
  • The purpose of this paper is to obtain new complexity results for a second-order cone optimization (SOCO) problem. We define a proximity function for the SOCO by a kernel function. Furthermore we formulate an algorithm for a large-update primal-dual interior-point method (IPM) for the SOCO by using the proximity function and give its complexity analysis, and then we show that the new worst-case iteration bound for the IPM is $O(q\sqrt{N}(logN)^{\frac{q+1}{q}}log{\frac{N}{\epsilon})$, where $q{\geqq}1$.

Study on Aerodynamic Optimization Design Process of Multistage Axial Turbine

  • Zhao, Honglei;Tan, Chunqing;Wang, Songtao;Han, Wanjin;Feng, Guotai
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.130-135
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    • 2008
  • An aerodynamic optimization design process of multistage axial turbine is presented in this article: first, applying quasi-three dimensional(Q3D) design methods to conduct preliminary design and then adopting modern optimization design methods to implement multistage local optimization. Quasi-three dimensional(Q3D) design methods, which mainly refer to S2 flow surface direct problem calculation, adopt the S2 flow surface direct problem calculation program of Harbin Institute of Technology. Multistage local optimization adopts the software of Numeca/Design3D, which jointly adopts genetic algorithm and artificial neural network. The major principle of the methodology is that the successive design evaluation is performed by using an artificial neural network instead of a flow solver and the genetic algorithms may be used in an efficient way. Flow computation applies three-dimensional viscosity Navier Stokes(N-S) equation solver. Such optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid. Such process was applied to optimize a three-stage axial turbine. During the optimization, blade shape and meridional channel were respectively optimized. Through optimization, the total efficiency increased 1.3% and total power increased 2.4% while total flow rate only slightly changed. Therefore, the total performance was improved and the design objective was achieved. The preliminary design makes use of quasi-three dimensional(Q3D) design methods to achieve most reasonable parameter distribution so as to preliminarily enhance total performance. Then total performance will be further improved by adopting multistage local optimization design. Thus the design objective will be successfully achieved without huge expenditure of manpower and calculation time. Therefore, such optimization design process may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.

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Efficiency Optimization Control of SynRM with ANN Speed Estimation (ANN의 속도 추정에 의한 SynRM의 효율 최적화 제어)

  • Choi, Jung-Sik;Ko, Jae-Sub;Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.55 no.3
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    • pp.133-140
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    • 2006
  • This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor(SynRM) which minimizes the copper and iron losses. Also, this paper presents a speed estimated control scheme of SynRM using artificial neural network(ANN). There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of ANN is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

Efficiency Optimization Control for High Performance Operation of Synchronous Reluctance Motor (동기 리럭턴스 전동기의 고성능 운전을 위한 효율 최적화 제어)

  • 정동화;이정철;이홍균
    • Journal of the Korean Society of Safety
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    • v.16 no.2
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    • pp.51-56
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    • 2001
  • This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor (SynRM) which minimizes the copper and iron losses. fen exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. Simulation results are presented to show the validity of the proposed algorithm.

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Optimization of 'Patterned Ground Shield' of Spiral Inductor using Taguchi's Method (다구찌 실험 계획법을 이용한 나선형 인덕터의 패턴드 그라운드 쉴드 최적 설계 연구)

  • Ko, Jae-Hyeong;Oh, Sang-Bae;Kim, Dong-Hun;Kim, Hyeong-Seok
    • 한국정보통신설비학회:학술대회논문집
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    • 2007.08a
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    • pp.436-439
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    • 2007
  • This paper describes the optimization of PGS(Patterned Ground Shield) of 5.5 turns rectangular spiral inductor using Taguchi's method. PGS is decrease method of parasite component by silicon substrate among dielectric loss reduction method. By using the taguchi's method, each parameter is fixed upon that PGS high poison(A), slot spacing(B), strip width(C) and overlap turn number(D) of PGS design parameter. Then we verified that percentage contribution and design sensitivity analysis of each parameter and level by signal to noise ratio of larger-the-better type. We consider percentage contribution and design sensitivity of each parameter and level, and then verify that model of optimization for PGS is lower inductance decreasing ratio and higher Q-factor increasing ratio by EM simulation.

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Comparison of Evolutionary Computation for Power Flow Control in Power Systems (전력계통의 전력조류제어를 위한 진화연산의 비교)

  • Lee, Sang-Keun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.54 no.2
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    • pp.61-66
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    • 2005
  • This paper presents an unified method which solves real and reactive power dispatch problems for the economic operation of power systems using evolutionary computation such as genetic algorithms(GA), evolutionary programming(EP), and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most of these approaches have the common defect of being caught to a local minimum solution. The proposed methods, applied to the IEEE 30-bus system, were run for 10 other exogenous parameters and composed of P-optimization module and Q-optimization module. Each simulation result, by which evolutionary computations are compared and analyzed, shows the possibility of applications of evolutionary computation to large scale power systems.

Topology optimization of Reissner-Mindlin plates using multi-material discrete shear gap method

  • Minh-Ngoc Nguyen;Wonsik Jung;Soomi Shin;Joowon Kang;Dongkyu Lee
    • Steel and Composite Structures
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    • v.47 no.3
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    • pp.365-374
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    • 2023
  • This paper presents a new scheme for constructing locking-free finite elements in thick and thin plates, called Discrete Shear Gap element (DSG), using multiphase material topology optimization for triangular elements of Reissner-Mindlin plates. Besides, common methods are also presented in this article, such as quadrilateral element (Q4) and reduced integration method. Moreover, when the plate gets too thin, the transverse shear-locking problem arises. To avoid that phenomenon, the stabilized discrete shear gap technique is utilized in the DSG3 system stiffness matrix formulation. The accuracy and efficiency of DSG are demonstrated by the numerical examples, and many superior properties are presented, such as being a strong competitor to the common kind of Q4 elements in the static topology optimization and its computed results are confirmed against those derived from the three-node triangular element, and other existing solutions.

A Reinforcement Loaming Method using TD-Error in Ant Colony System (개미 집단 시스템에서 TD-오류를 이용한 강화학습 기법)

  • Lee, Seung-Gwan;Chung, Tae-Choong
    • The KIPS Transactions:PartB
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    • v.11B no.1
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    • pp.77-82
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    • 2004
  • Reinforcement learning takes reward about selecting action when agent chooses some action and did state transition in Present state. this can be the important subject in reinforcement learning as temporal-credit assignment problems. In this paper, by new meta heuristic method to solve hard combinational optimization problem, examine Ant-Q learning method that is proposed to solve Traveling Salesman Problem (TSP) to approach that is based for population that use positive feedback as well as greedy search. And, suggest Ant-TD reinforcement learning method that apply state transition through diversification strategy to this method and TD-error. We can show through experiments that the reinforcement learning method proposed in this Paper can find out an optimal solution faster than other reinforcement learning method like ACS and Ant-Q learning.

Minimization of Fuel Cost by Optimal P-Q Generation in Three-Bus System (3 모선 시스템의 유무효 발전력 최적분담을 통한 연료비 최소화)

  • Lee, Sang-Joong;Yang, Seong-Deog
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.19 no.1
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    • pp.40-43
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    • 2005
  • This paper presents the minimization of the fuel cost by optimal allocation of P-Q generation in a three-bus sample system. Derivation of the system loss sensitivities by optimization technique is introduced. The loss sensitivities are substituted into the optimality conditions and the optimal P-Q allocation is computed to obtain the minimal fuel cost.