• Korean Journal of Veterinary Research
• /
• v.46 no.2
• /
• pp.159-164
• /
• 2006

A stochastic simulation model incorporated with Reed-Frost approach was derived for evaluating diagnostic performance of a test used for a screening program of an infectious disease. The Reed-Frost model was used to characterize the within-herd spread of the disease using a hypothetical example. Specifically, simulation model was aimed to estimate the number infected animals in an infected herd, in which imperfect serologic tests are performed on samples taken from herds and to illustrate better interpreting survey results at herd-level when uncertainty inevitably exists. From a risk analysis point of view, model output could be appropriate in developing economic impact assessment models requiring probabilistic estimates of herd-level performance in susceptible populations. The authors emphasize the importance of knowing the herd-level diagnostic performance, especially in performing emergency surveys in which immediate control measures should be taken following the survey. In this context this model could be used in evaluating efficacy of a survey program and monitoring infection status in the area concerned.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.144-147
• /
• 2000

In this paper, we propose two receiver structures of the impulse radio (IR) system to improve its performance in multipath environments. Recently, the impulse radio system has drawn much attention for future high-speed wire-less communication services. The conventional IR receiver directly correlates received signals with the ideal reference waveform, which results in performance degradation in multipath environments. The Key idea of the proposed receiver structures is to reflect the multipath Characteristics into the IR receiver. One is to deconvolve the received waveform with estimates of the multipath gains to obtain the transmitted waveform while the other is to modify the reference waveform of the correlator according to the estimates of the multipath gains. We examine the performance of the proposed schemes for the statistical indoor wireless communication channel model using computer simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1659-1663
• /
• 1991

A new control design methodology is presented here which is based on a nonlinear time-series reference model. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible a.c. transmission system (FACTS) with series capacitor power feedback control is studied. A bilinear auto-regressive moving average (BARMA) reference model is identified from system data and the feedback control manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index (J). A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack. These applications are typical of the numerous plants for which nonlinear adaptive control has the potential to provide significant performance improvements. For aircraft control, significant maneuverability gains can provide safer transportation under large windshear disturbances as well as tactical advantages. For FACTS, there is the potential for significant increase in admissible electric power transmission over available transmission lines along with energy conservation. Electric power systems are inherently nonlinear for significant transient variations from synchronism such as may result for large fault disturbances. In such cases, traditional linear controllers may not stabilize the swing (in rotor angle) without inefficient energy wasting strategies to shed loads, etc. Fortunately, the advent of power electronics (e.g., high-speed thyristors) admits the possibility of adaptive control by means of FACTS. Line admittance manipulation seems to be an effective means to achieve stabilization and high efficiency for such FACTS. This results in parametric (or multiplicative) control of a highly nonlinear plant.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.4
• /
• pp.154-157
• /
• 2006

This paper is proposed hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design..of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2005.11a
• /
• pp.315-320
• /
• 2005

This paper is proposed adaptive fuzzy-neuro controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of nor measured between the motor speed and output of a reference model. The control performance of the adaptive fuzy-neuro controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Journal of Power Electronics
• /
• v.15 no.5
• /
• pp.1274-1285
• /
• 2015

This paper deals with model reference adaptive system (MRAS) speed estimators based on a secondary flux for linear induction motors (LIMs). The operation of these estimators significantly depends on an adaptation mechanism. Fixed-gain PI controller is the most common adaptation mechanism that may fail to estimate the speed correctly in different conditions, such as variation in machine parameters and noisy environment. Two adaptation mechanisms are proposed to improve LIM drive system performance, particularly at very low speed. The first adaptation mechanism is based on fuzzy theory, and the second is obtained from an LIM mechanical model. Compared with a conventional PI controller, the proposed adaptation mechanisms have low sensitivity to both variations of machine parameters and noise. The optimum parameters of adaptation mechanisms are tuned using an offline method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The efficiency of MRAS speed estimator is validated by both numerical simulation and real-time hardware-in-the-loop (HIL) implementations. Results indicate that the proposed adaptation mechanisms improve performance of MRAS speed estimator.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.569-572
• /
• 1996

Explicit state-space formulate for an H$_{.inf}$ based two-degrees-of-freedom robust controller are derived in discrete-time. The controller provides robust stability against coprime factor uncertainty, and a degree of robust performance in the sense of making the closed-loop system match a prespecified reference model. It is shown that the controller consists of a plant observer, the chosen reference model, and a generalized state feedback law associated with the plant and model states. The controller structure is shown to be relatively simple and thus may reduce the computational load on the digital control processor.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.7
• /
• pp.1360-1365
• /
• 2011

Electro-hydraulic servo motor is used to a lot of in the field of industrial equipment which requires one of the control functions among pressure, flow, and power output. In this paper, linear discrete reference model of the electro-hydraulic servo motor system are made for 1-step ahead predictive control. The parameters of electro-hydraulic servo motor system are estimated using the recursive least square method. 1-step ahead predictive model output of electro-hydraulic servo motor system corresponded to reference model output in spite of estimated parameters are not meet real parameters. Control performance affections are studied due to the forgetting factors variation.

• Management & Information Systems Review
• /
• v.3
• /
• pp.1-14
• /
• 1999

Recently, information resource management(IRM) has a considerable interest among researchers and practitioners because the information resource have been found critical influence on organizational performance. The IRM construct has been defined a comprehensive approach to planning, organizing, controlling the resources, and activities associated with acquiring and distributing data to meet a business need. This study have several objectives: 1) to operationalize the measurement instrument of IRM, 2) to identify the factors influencing organizational performance, and 3) to suggest the research model between IRM and organizational performance and then 4) to provide reference for managers to assess the IRM implementation in their organization. By reviewing the literature, past experience, others' use, encouragement by others, and anxiety are selected as the factors influencing IRM. The IRM construct has been classified with eight dimensions : chief information officer, planning, security, technology integration, advisory committees, enterprise model, information integration, and data administration. Eight hypotheses concerning the relationship between each of the IRM and organizational performance are suggested in this study.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.1
• /
• pp.115-126
• /
• 1996

In the time optimal control problem, bang-bang control has been used becaese it is the theoretical time minimum solution. However, to improve tracking speed performance in the time optimal control, it is important to select a switching point accurately which makes the velocity zero near the target track. But it is not easy to select the swiching point accurately because of the damping coefficient variation and uncertainties of modeling an actual system. The Adaptive model following control(AMFC) is implemented to relieve the difficulty and inconvenience of this task. The AMFC and make the controlled plant follow as closely as possible to a desired reference model whose switching point can be calculated easily and accurately, assuring the error between the states of the reference model and those of the controlled plant appoaches zero. The hybrid control method composed of AMFC and PID is applied to a tracking actuator of the magneto optical disk drive(MODD) in random access devices to improve its slow tracking performance. According to the simulaion and experimental results, the average tracking time as small as 20ms is obtained for a 3.5 magneto-optical disk drive. The AMFC also can be applied for other random access devices to improve the average tracking performance.