• Title/Summary/Keyword: Operating parameter

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A Study on the Analysis of TEB Local Planner Parameters to Improve the Target Reach Time of Autonomous Mobile Robot (자율주행 이동로봇의 목표 도달 시간을 개선하기 위한 TEB Local Planner 파라미터의 분석에 관한 연구)

  • Roh, Hyeong-Seok;Jung, Ui;Han, Jung-Min;Jeon, Jung-Hyeon;Jeon, Ho-Nam
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.5
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    • pp.853-859
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    • 2022
  • In this study, we analyzed the instantaneous trajectory generation capability and target arrival rate of a mobile robot by changing the parameter of the TEB (Timed Elastic Band) Local Planner among local planners that affect the instantaneous obstacle avoidance ability of the mobile robot using ROS (Robot Operating System) simulation and real experience. As a result, we can expect a decrease in the target arrival time of the mobile robot through a decrease in the parameter values of the TEB Local Planner's min_obstacle_dist, inflation_dist, and penalty_epsilon. However, if this parameter is reduced too much, the risk of obstacle collision of the moving robot is increases, so it is important to combine the appropriate values to construct the parameter.

An Alternative Optimization Procedure for Parameter Design

  • Kwon, Yong Man
    • Journal of Integrative Natural Science
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    • v.12 no.3
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    • pp.69-73
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    • 2019
  • Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

Evaluation of Coagulants Dispersion in Pump Diffusion Mixer for Water Treatment (CFD모사 기법을 이용한 Pump Diffusion Mixer내의 응집체 확산분포에 대한 평가)

  • Park, Young-Oh;Park, No-Suk;Kim, Seong-Su;Kim, Ki-Don;Lim, Kyung-Ho
    • Journal of Korean Society of Water and Wastewater
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    • v.22 no.1
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    • pp.49-63
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    • 2008
  • The objectives of this research were to evaluate the pressurized/the main inlet water flowrate ratio which have been used as the most important parameter for operating the pump diffusion mixer until now, to suggest the alternative operating parameter and the relating criteria if the flowrate ratio was not inadequate. For the objectives of this research, computational fluid dynamics (CFD) simulation was conducted for 21 cases of flowrate ratio in full-scaled pump diffusion mixer. From the results of CFD simulation, the local velocity gradient values were calculated in each case in order to analyze the simulation results in more detail. For verifying CFD simulation, wet test was conducted. The wet test was to measure the factual coagulant dispersion distribution at a distance of 5.4m from deflector. From both results of CFD simulation and wet test, flowrate ratio was inadequate as operating parameter or criteria, on the other hand the pressurized/the main inlet velocity ratio(dimensionless) was useful in predicting the performance of pump diffusion mixer. Also, the injected coagulant could be dispersed evenly in overall cross section on the condition that pressurized/the main inlet velocity ratio(dimensionless) is over at least 20.

An Algorithm for Robust Noninteracting Control of Ship Propulsion System

  • Kim, Young-Bok
    • Journal of Mechanical Science and Technology
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    • v.14 no.4
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    • pp.393-400
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    • 2000
  • In this paper, a new algorithm for noninteracting control system design is proposed and applied to ship propulsion system control. For example, if a ship diesel engine is operated by consolidated control with controllable pitch propeller (CPP), the minimum fuel consumption is achieved satisfying the demanded ship speed. For this, it is necessary that the ship is operated on the ideal operating line which satisfies the minimum fuel consumption, and the both pitch angle of CPP and throttle valve angle are controlled simultaneously. In this context of view, this paper gives a controller design method for a ship propulsion system with CPP based on noninteracting control theory. Where, linear matrix inequality (LMI) approach is introduced for the control system design to satisfy the given $H_{\infty}$, constraint in the presence of physical parameter perturbation and disturbance input. To the end, the validity and applicability of this approach are illustrated by the simulation in the all operating ranges.

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A Method of Tuning Optimization for PID Controller in Nuclear Power Plants (원자력발전소 PID 공정제어기에 대한 튜닝 최적화 방법)

  • Sung, Chan Ho;Min, Moon Gi
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.10 no.1
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    • pp.1-6
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    • 2014
  • PID(Proportional, Integral, Derivative) controller is one of the most used process controllers in nuclear power plants. The optimized parameter setting of process controller contributes to the stable operation and efficiency in the operating nuclear power plants. PID parameter setting is tuned when new process control system is established or process control system is changed. It is a burdensome work for I&C(Instrument and Control) engineers to tune the PID controller because it requires a lot of experience and knowledge. When the plant is in operation, inadequate PID parameter setting can be the cause of the unstable process of the plant. Therefore the results of PID parameter setting should be compared, simulated, verified and finally optimized. The practical PID tuning methods used in process controller are tuning operation calculation(Ziegler-Nicholes, Minimum TIAE, Lambda, IMC), exclusive tuning program based on computer and Matlab application. This paper introduces the various tuning methods and suggests an optimized PID tuning process in the operating nuclear power plants.

Study on the Prediction Technique of Vehicle Performance using Parameter Analysis (파라미터 해석을 통한 차량 성능 예측 기법 연구)

  • Kim, Ki-Chang;Kim, Chan-Mook;Kim, Jin-Taek
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2009.10a
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    • pp.647-653
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    • 2009
  • Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used SN (Signal to Noise) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. This paper describes the prediction technique of vehicle performance using parameter analysis to reduce man hour and test development period as well as to achieve stable NVH performance. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce the time needed to develop better vehicles.

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Neural Network for on-line Parameter Estimation of IPMSM Drive (IPMSM 드라이브의 온라인 파라미터 추정을 위한 신경회로망)

  • 이홍균;이정철;정동화
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.53 no.5
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    • pp.332-337
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    • 2004
  • A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

On-line Parameter Estimation of IPMSM Drive using Neural Network (신경회로망을 이용한 IPMSM 드라이브의 온라인 파라미터 추정)

  • Choi, Jung-Sik;Ko, Jae-Sub;Chung, Dong-Hwa
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.5
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    • pp.429-433
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    • 2007
  • A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

Alternative Optimization Procedure to Parameter Design (파라미터 설계에 대한 최적화 대체방안)

  • Kwon, Yong-Man;Chang, Duk-Soon
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.1
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    • pp.11-18
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    • 2001
  • Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used signal-to-noise(SN) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many statisticians criticize the Taguchi techniques of analysis, particularly those based on SN ratio. In this paper we propose a substantially simpler optimization procedure for parameter design without resorting to SN ratio.

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On-line Parameter Estimation of IPMSM Drive using Neural Network (신경회로망을 이용한 IPMSM 드라이브의 온라인 파라미터 추정)

  • Choi, Jung-Sik;Ko, Jae-Sub;Lee, Jung-Ho;Kim, Jong-Kwan;Park, Ki-Tae;Park, Byung-Sang;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.207-209
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    • 2006
  • A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

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