• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.241-247
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• 2000

The reference model of an MRC (model reference control) provides the desired trajectory a plant should follow and thus the design of a reference model has a significant effect on control performance. In most control systems control input to a plant has some bounds and it is preferable to make use of as large control inputs as possible within the range of no saturation. In this paper a new approach of selecting the reference model is proposed for bounded control inputs. Design variables of the reference model are determined in such a way that maximizes the performance index within the range of no saturation. Moreover this variable reference model is regularly updated during control. This scheme is verified by application to the servo motor position control system in various simulations. The responses of the MRC with a variable reference model show better tracking performance than that with a fixed reference mode. Moreover by adjusting the update interval of the reference model the control performance can be further improved.

• Journal of Power System Engineering
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• v.11 no.3
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• pp.66-72
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• 2007

This study proposed new method to decide the reference model necessary for design PID controller. In generally, control design problems using the reference model have the following two factors. One factor is that numerical model of the controlled system can be obtained extremely, and the other is that specification for the closed-loop dynamic performance is pure moderate. Therefore, the control design procedure is essentially based on the partial reference model matching which offers a reasonable method to simplify the design and the controller configuration under the controlled system uncertainty. ITAE(Integral of time-multiplied absolute error) performance index and Kitamori method etc. which were used a reference model method had a limit to settling time and rising time of reference model that it arrived to steady state response according to the controlled system. On this study, if it only knew peak time of overshoot and settling time by measurement signal of the controlled system, it can be made the reference model easily. We proposed new method to improve performance index of the reference model superior to existing reference model index and illustrate the numerical simulation results to show the effectiveness of proposed control method design.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.947-950
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• 2007

Recently, most of the public institutions are developing ITA(Information Technology Architecture) & BSC (Balance ScoreCard) system. ITA's reference model is provided for the consistency, reusability, and interoperability. By the way, PRM(Performance Reference Model), one of the ITA reference models, is needed to link with BSC system. In this paper, we provide the linking method of ITA and BSC.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.166-173
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• 1999

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.79-85
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• 2015

Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

• Journal of Information Technology Services
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• v.6 no.2
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• pp.161-175
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• 2007

Face recognition technology has lately attracted considerable attention because of its non-intrusiveness, usability and applicability. Related companies insist that their commercial products show the recognition rates more than 95% according to their self-testing. But, the rates cannot be admitted as official recognition rates. So, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of face recognition systems. In this paper, I propose a reference model for biometrics recognition evaluation tools, and implement an evaluation tool for the face recognition system based on the proposed reference model.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.3
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• pp.215-223
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• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller fur a vector controlled induction motor drive. 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 model reference adaptive control(MRAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the Proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.70-76
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• 2006

The objective of this paper is to propose a reference model of a fire detection and monitoring system using MS/TP protocol. The reference model is designed to satisfy the requirements of response time and flexibility. The reference model is operated on the basis of BACnet, a standard communication protocol for building automation systems. Validity of the reference model was examined using a simulation model. This study also evaluated the performance of the BACnet-based fire detection and monitoring system in terms of network-induced delay. Simulation results show that the reference model satisfies the requirements of the fire detection and monitoring system.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.92-99
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• 1997

A model reference adaptive control(MRAC) theory is very useful for controlling a plant of which the parameters are unknown or vary during operation usint only input-output signal of plant. In this study, 2' nd order discreter time MRAC controller is designed for an electrohydraulic position control system which is represented with nonlinear mathematical model and the least square method is adopted for the para-meter adjustment law. This control algorthm is applied to the position control of electrohydraulic servosystem through computer simulation and the effect of the change of load, sampling time upon the performance following reference model and upon the performance of estimating plant parameters are examined.

• Korean Journal of Radiology
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• v.24 no.2
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• pp.155-165
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• 2023

Objective: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the concordance of expert-determined standards with a clinical gold standard (herein, pathological confirmation) and the effects of different expert-determined reference standards on the estimates of radiologists' diagnostic performance to detect malignant pulmonary nodules on chest radiographs with and without the assistance of a DLAD model. Materials and Methods: This study included chest radiographs from 50 patients with pathologically proven lung cancer and 50 controls. Five expert-determined standards were constructed using the interpretations of 10 experts: individual judgment by the most experienced expert, majority vote, consensus judgments of two and three experts, and a latent class analysis (LCA) model. In separate reader tests, additional 10 radiologists independently interpreted the radiographs and then assisted with the DLAD model. Their diagnostic performance was estimated using the clinical gold standard and various expert-determined standards as the reference standard, and the results were compared using the t test with Bonferroni correction. Results: The LCA model (sensitivity, 72.6%; specificity, 100%) was most similar to the clinical gold standard. When expert-determined standards were used, the sensitivities of radiologists and DLAD model alone were overestimated, and their specificities were underestimated (all p-values < 0.05). DLAD assistance diminished the overestimation of sensitivity but exaggerated the underestimation of specificity (all p-values < 0.001). The DLAD model improved sensitivity and specificity to a greater extent when using the clinical gold standard than when using the expert-determined standards (all p-values < 0.001), except for sensitivity with the LCA model (p = 0.094). Conclusion: The LCA model was most similar to the clinical gold standard for malignant pulmonary nodule detection on chest radiographs. Expert-determined standards caused bias in measuring the diagnostic performance of the artificial intelligence model.