• Title/Summary/Keyword: cost estimator

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Speed Control of Induction Motor Using Flux Compensation In Model Reference Adaptive System (FMRAS에 보상기를 이용한 유도전동기 속도제어)

  • Seo Young-Soo;Lee Chun-Sang
    • Proceedings of the KIPE Conference
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    • 2002.07a
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    • pp.200-204
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    • 2002
  • When the vector control, which does not need a speed? signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of flux model reference adaptive system. The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the two model are introduced to perform accurate rotor speed estimation. Simulation result show the validity of the proposed control method.

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A Modified Target Costing Technique to Improve Product Quality from Cost Consideration

  • Wu, Hsin-Hung
    • International Journal of Quality Innovation
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    • v.6 no.2
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    • pp.31-45
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    • 2005
  • The target costing technique, mathematically discussed by Sauers, only uses the $C_p$ index along with Taguchi loss function and ${\bar{X}}-R$ control charts to set up goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p$ value to ${\bar{X}}-R$ control charts to obtain goal control limits. This study further considers the reflected normal loss function as well as the $C_{pk}$ index along with its lower confidence interval in forming goal control limits. With the use of lower confidence interval to replace the point estimator of the $C_{pk}$ index and reflected normal loss function proposed by Spiring to measure the loss to society, this modified and improved target costing technique would become more robust and applicable in practice. Finally, an example is provided to illustrate how this modified and improved target costing technique works.

Decision Making Model for Optimal Earthwork Allocation Planning (최적 토량배분 계획을 위한 의사결정 모델)

  • Gwak, Han-Seong;Seo, Byoung-Wook;Lee, Dong-Eun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2016.05a
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    • pp.162-163
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    • 2016
  • This paper presents a mathematical model for optimizing earthwork allocation plan that minimizes earthwork cost. The model takes into account operational constraints in the real-world earthwork such as material-type (i.e., quality level of material) and quantities excavated from cut-sections, required quality of material and quantities for each embankment layer, top-down cutting and bottom-up filling constraints, and allocation orders. These constraints are successfully handled by assuming the rock-earth material as the three dimensional (3D) blocks. The study is of value to project scheduler because the model identifies the optimal earth allocation plan (i.e., haul direction (cut and fill pairs), quantities of soil, type of material, and order of allocations) expeditiously and is developed as an automated system for usability. It is also relevant to estimator in that it computes more realistic earthworks costs estimation. The economic impact and validity of the mathematical model was confirmed by performing test cases.

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Control Variates for Percentile Estimation of Project Completion Time in PERT Network (통제변수를 이용한 PERT 네트워크에서 프로젝트 완료확률의 추정)

  • 권치명
    • Journal of the Korea Society for Simulation
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    • v.9 no.4
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    • pp.67-75
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    • 2000
  • Often system analysts are interested in the estimation of percentile for system performance. For instance, in PERT network system, the percentile that the project. Typically the control variate method is used to reduce the variability of mean response using the correlation between the response and the control variates with a little additional cost during the course of simulation. In the same spirit, we apply this method to estimate the percentile of project completion time in PERT system, and evaluate the efficiency of the controlled estimator for its percentile.1 Simulation results indicate that the controlled estimators are more effective in reducing the variances of estimators than the simple estimators, however those tend to a little underestimate the percentiles for some critical values. We need more simulation experiments to examine such a kind of bias problem. We expect this research presents a step forward in the area of variance reduction techniques of stochastic simulation.

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Control of Single Propeller Pendulum with Supervised Machine Learning Algorithm

  • Tengis, Tserendondog;Batmunkh, Amar
    • International journal of advanced smart convergence
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    • v.7 no.3
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    • pp.15-22
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    • 2018
  • Nowadays multiple control methods are used in robot control systems. A model, predictor or error estimator is often used as feedback controller to control a robot. While robots have become more and more intensive with algorithms capable to acquiring independent knowledge from raw data. This paper represents experimental results of real time machine learning control that does not require explicit knowledge about the plant. The controller can be applied on a broad range of tasks with different dynamic characteristics. We tested our controller on the balancing problem of a single propeller pendulum. Experimental results show that the use of a supervised machine learning algorithm in a single propeller pendulum allows the stable swing of a given angle.

Design of a State Feedback Controller with a Current Estimator in Brushless DC Motors (전류추정기에 의한 브러시리스 직류전동기의 상태변수 궤환제어기 설계)

  • Oh, Tae-Seok;Shin, Yun-Su;Kim, Il-Hwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.6
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    • pp.589-595
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    • 2007
  • This paper presents a new method on controller design of brushless dc motors. In such drives the current ripples are generated by motor inductance in stator windings and the back EMF. To suppress the current ripples the current controller is generally used. To minimize the size and the cost of the drives it is desirable to control motors without the current controller and the current sensing circuits. To estimate the motor CUlTent it is modeled by a neural network that is contigured as an output-error dynamic system. The identified model is essentially a one step ahead prediction structure in which past inputs and outputs are used to calculate the current output. Using the model, a state feedback controller to compensate the effects of disturbance has been designed. The controller is implemented by a 16-bit microprocessor and the effectiveness of the proposed control method is verified through experiments.

Generalized Higher Order Energy Based Instantaneous Amplitude and Frequency Estimation and Their Applications to Power Disturbance Detection

  • Iem, Byeong-Gwan
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.162-166
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    • 2012
  • The instantaneous amplitude (IA) based on the higher order differential energy operator is proposed. And its general form for arbitrary order is also proposed. The various definitions of the IA and the instantaneous frequency (IF) estimators are considered. The IA and IF estimators based on the energy operators need less computational cost than the conventional IF and IA estimators exploiting the Hilbert transform. The IF and IA estimators are compared in terms of the frequency and amplitude tracking accuracy of the AM-FM signals. For noiseless case, the IA and IF estimators based on the Teager-Kaiser energy operator show better tracking performance than the IF and IA estimators based on the higher energy operators. However, under noisy condition, the IF and IA estimator based on the higher order energy operators with the order 3 and 4 show better tracking than the Teager-Kaiser energy based estimators. The IF and IA estimators are applied to signals in the various power anomalies to show their usefulness as the disturbance detectors.

Control Algorithm for PMSM using Rectangular Two Hall Sensors Compensated by Sensorless Control Method (센서리스 제어 기법에 의해 보완된 두 개의 구형파 홀센서를 이용한 PMSM 제어 알고리즘)

  • Lee, Jung-Hyo;Lee, Taek-Ki;Kim, Young-Ryul;Won, Chung-Yuen
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.26 no.5
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    • pp.40-47
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    • 2012
  • The PMSM position sensor using two rectangular hall sensors can restrictively acquire the 90[$^{\circ}$] position information of rotor according to electrical angle. Thus, the control method using this position sensor cannot react properly to a rapid load torque change. On the other hand, even though a sensorless method has the advantage of acquiring instantaneous rotor position information, the accuracy of position sensor can be determined by the gain value of estimator. This paper suggests a robust speed control method on torque fluctuation condition, which combines low cost two rectangular hall sensors and sensorless control method.

Vector Control for Speed Estimate of Hyperstable MRAS (Hyperstable MRAS 방식의 속도 추정을 위한 벡터제어)

  • Seo Young-Soo;Kim Eun-Gi;Kim Yong-Ju;Kim Young-Jin
    • Proceedings of the KIPE Conference
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    • 2001.07a
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    • pp.409-412
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    • 2001
  • When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. In this paper, describes a rotor speed estimate method of induction motor based on the theory of counter EMF MRAS. This method eliminated the pure integrator. and we can be expected to rapid responsibility of the speed Identification. Therefore, we improve the initial condition of the integrator and drift problem. The stability of speed estimator is proved on the basis of hyperstability theory. In order to confirm the performance of the proposed system. Simulation and experiment is performed.

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ON THE DETERMINANTS OF ENTREPRENEURSHIP IN MIDDLE EAST AND NORTH AFRICA

  • Zmami, Mourad;Salha, Ousama Ben
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.181-187
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    • 2021
  • The purpose of this study is to examine empirically the short- and long-run determinants of entrepreneurial activity in a sample of 15 the Middle East and North African economies between 2006 and 2018. More specifically, four groups of determinants are considered in the analysis, namely economic, demographic, business environment, and institutional. Given the autoregressive feature of the entrepreneurial activity process, a dynamic panel data model is estimated using the system GMM estimator. Findings reveal that unemployment, trade openness, population density, and economic freedom are the main drivers of new business creation in the short-run, while the cost and number of procedures to start a new business negatively affect entrepreneurship. In the long-run, the same findings hold true. Moreover, education and political stability and the absence of violence/terrorism positively affect entrepreneurial activity. Policy recommendations are accordingly designed.