• Title/Summary/Keyword: Optimal tuning

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Optimal Multicast Algorithm and Architecture-Dependent Tuning on the Parameterized Communication Model (변수화된 통신모델에서의 최적의 멀티캐스트 알고리즘 및 컴퓨터 구조에 따른 튜닝)

  • Lee, Ju-Yeong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.9
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    • pp.2332-2342
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    • 1999
  • Multicast is an important system-level one-to-many collective communication service. A key issue in designing software multicast algorithms is to consider the trade-off between performance and portability. Based on the LogP model, the proposed parameterized communication model can more accurately characterize the communication network of parallel platforms, Under the parameterized model, we propose an efficient architecture-independent method. OPT-tree algorithm, to construct optimal multicast trees and also investigate architecture-dependent tuning on performance of the multicast algorithm to achieve the truly optimal performance when implemented in real networks. Specifically, OPT-mesh which is the optimized version of the parameterized multicast algorithm for wormhole-switched mesh networks is developed and compared with two other well-known network-dependent algorithms.

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Fuzzy neural network modeling using hyper elliptic gaussian membership functions (초타원 가우시안 소속함수를 사용한 퍼지신경망 모델링)

  • 권오국;주영훈;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.442-445
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    • 1997
  • We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

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Control Gain Tuning of the 3-DOF Micro Parallel Mechanism Platform Via Design of Experiment Methodology (실험계획법을 이용한 3 자유도 마이크로 병렬기구 플랫폼의 제어 이득 선정)

  • Seo, Tae-Won
    • Journal of the Korean Society for Precision Engineering
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    • v.29 no.11
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    • pp.1207-1213
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    • 2012
  • Typically commercial controllers do not give data of the controller gains. Therefore, it is very hard to determine the optimal controller gain even though the dynamic model is derived. In this case, design of experiment (DOE) methodology can be a powerful tool for gain tuning. In this research, gain tuning process is proposed based on the DOE. Micro parallel mechanism platform with 3 degrees-of-freedom (DOF) is used for the experiments. Controller gains are measured indirectly from the voltages of adjustable resistors. The controller gains of three actuators are optimized by two or three steps, respectively. The correlations of the controller gains are also analyzed. The process and methodology can be adopted in gain tuning of other mechanical systems.

Auto Tuning of PID for RO System Using Immune Algorithm (면역 알고리즘을 이용한 RO 공정 PID 제어기의 자동 튜닝)

  • Kim, Go-Eun;Park, Ji-Mo;Kim, Jin-Sung;Kwon, O-Shin;Heo, Hoon
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.19 no.11
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    • pp.1103-1109
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    • 2009
  • In this paper, the control of a membrane used in reverse osmosis desalination plant by using immune algorithm(IA) is addressed. The proposed algorithm IA of auto tuning method can find optimal gains and compared with conventional Ziegler-Nichols tuning method. The results of computer simulation represent that the proposed IA shows a good control performances better than Ziegler-Nichols tuning method.

Multiobjective PI Controller Tuning of Multivariable Boiler Control System Using Immune Algorithm

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.1
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    • pp.78-86
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    • 2003
  • Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

Development of Experimental Gain Tuning Technique for Multi-Axis Servo System (다축 서보 시스템의 Gain Tuning에 관한 연구)

  • Chung W.J.;Kim H.G.;Seo Y.G.;Lee K.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2006.05a
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    • pp.271-272
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    • 2006
  • This paper presented a new experimental gain tuning technique for a Multi-Axis Servo System. First, the investigation for proportional gain of velocity control loop by using a Dynamic Signal Analyzer (DSA) was performed. Using the FUNCTION characteristic of DSA based on the Bode plot, the Bode plot of open loop transfer function was obtained. In turn, the integral gain of a servo controller can be found out by using the Integration time constant extracted from the Bode plot of open loop transfer function. In the meanwhile, the positional gain of the servo controller has been obtained by using the Bode plot of the closed loop transfer function. We have also proposed the technique to find out an optimal parameter of a notch filter, which has a great influence on vibration reduction, by using the damping factor extracted from the Bode plot of closed loop transfer function.

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Robust Tuning of PID Controller With Disturbance Rejection Using Bacterial Foraging Based Optimization

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1092-1097
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    • 2005
  • In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on $H_{\infty}$ are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response

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Optimal Control of Gantry Crane Using Genetic Programming (유전프로그래밍에 의한 겐트리 크레인의 최적제어에 관한 연구)

  • 이영진;배종일;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 1998.10a
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    • pp.153-158
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    • 1998
  • In this paper, we present a design of optimal 2-DOF PID controller for control of gantry crane which has to control swing motion and trolley position. For tuning the parameter of 2-DOF PID controller, we used evolution strategy(ES). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.

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Evaluation and analytical approximation of Tuned Mass Damper performance in an earthquake environment

  • Tributsch, Alexander;Adam, Christoph
    • Smart Structures and Systems
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    • v.10 no.2
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    • pp.155-179
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    • 2012
  • This paper aims at assessing the seismic performance of Tuned Mass Dampers (TMDs) based on sets of recorded ground motions. For the simplest configuration of a structure-TMD assembly, in a comprehensive study characteristic response quantities are derived and statistically evaluated. Optimal tuning of TMD parameters is discussed and evaluated. The response reduction by application of a TMD is quantified depending on the structural period, inherent damping of the stand-alone structure, and ratio of TMD mass to structural mass. The effect of detuning on the stroke of the TMD and on the structural response is assessed and quantified. It is verified that a TMD damping coefficient larger than the optimal one reduces the peak deflection of the TMD spring significantly, whereas the response reduction of the main structure remains almost unaffected. Analytical relations for quantifying the effect of a TMD are derived and subsequently evaluated. These relations allow the engineer in practice a fast and yet accurate assessment of the TMD performance.

Intelligent Auto-Tuning for Adaptive Control of DC Motor System with Load Inertia of Great Variation

  • Woraphojn Khongphasook;Vipan Prijapanij;anant, Phornsuk-Ratiroch;Jongkol Ngamwiwit;Hiroshi Hirata
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.442-442
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    • 2000
  • The intelligent auto-tuning method fur a strongly stable adaptive control system of a DC motor with great load inertia variation is proposed. The stable characteristic polynomial that is designed by an optimal servo is specified for the adaptive pole placement control system. The appropriate adaptive control system can be derived, by adjusting automatically the weight of a performance criterion in optimal control by means of the fuzzy inference on the basis of the stability index.

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