• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.558-565
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• 2011

Various robot platforms have been designed and developed to perform given tasks in a hazardous environment for surveillance, reconnaissance, search and rescue, etc. We considered a terrain-adaptive and transformable hybrid robot platform that is equipped with rapid navigation capability on flat floors and good performance in overcoming stairs or obstacles. The navigation mode transition is determined and implemented by adaptive driving mode control of the mobile robot. In order to maximize the usability of wheel-track hybrid robot platform, we propose a terrain-adaptive and user-friendly remote controller and verify the efficiency and performance through its navigation performance experiments in real and test-bed environments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.3
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• pp.112-119
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• 2001

This paper proposes an adaptive reclosing scheme which is based on the classification of fault patterns. In case that the first reclosing is unsuccessful in distribution system employing with two-shot reclosing scheme, the proposed method can determine whether the second reclosing will be attempted of not. If the first reclosing is unsuccessful two fault currents can be measured before the second reclosing is attempted, where these two fault currents are utilized for an adaptive reclosing scheme. Total harmonic distortion and RMS are used for extracting the characteristics of two fault currents. And the pattern of two fault currents is respectively classified using a mountain clustering method a minimum-distance classifier. Mountain clustering method searches the cluster centers using the acquired past data. And minimum-distance classifier is used for classifying the measured two currents into one of the searched centers respectively. If two currents have the different pattern it is interpreted as temporary fault. But in case of the same pattern, the occurred fault is interpreted as permanent. The proposed method was tested for the fault data which had been measured in KEPCO's distribution system, and the test results can demonstrate the effectiveness of the adaptive reclosing scheme.

• Restorative Dentistry and Endodontics
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• v.42 no.1
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• pp.34-38
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• 2017

Objectives: The aim of this study was to evaluate the cyclic fatigue resistance of the ProTaper Universal D1 file (Dentsply Maillefer) under continuous and adaptive motion. Materials and Methods: Forty ProTaper Universal D1 files were included in this study. The cyclic fatigue tests were performed using a dynamic cyclic fatigue testing device, which had an artificial stainless steel canal with a $60^{\circ}$ angle of curvature and a 5 mm radius of curvature. The files were randomly divided into two groups (Group 1, Rotary motion; Group 2, Adaptive motion). The time to failure of the files were recorded in seconds. The number of cycles to failure (NCF) was calculated for each group. The data were statistically analyzed using Student's t-test. The statistical significant level was set at p < 0.05. Results: The cyclic fatigue resistance of the adaptive motion group was significantly higher than the rotary motion group (p < 0.05). Conclusion: Within the limitations of the present study, the 'Adaptive motion' significantly increased the resistance of the ProTaper Universal D1 file to cyclic facture.

• Child Health Nursing Research
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• v.28 no.3
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• pp.187-196
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• 2022

Purpose: This study aimed to clarify the factors related to mothers' decisions to provide disease explanations to their children, investigate the associations between those factors and social adaptive skills, and examine support relative to children's growth and development. Methods: Data were collected from anonymous, self-administered questionnaires answered by 71 mothers of outpatient school-aged children with congenital heart disease. The questionnaire items included characteristics of mothers and children, decision factors for providing disease explanations, and children's social adaptive skills (Asahide-Shiki social adaptive skills test). Factor analysis was performed on the decision factors, and multiple regression analysis was performed to examine the association between the identified factors and each social adaptive skill. Results: The decision factors for providing disease explanations were the mother's explanation ability, the receptive capability of the child, and the child's interest and literacy regarding the explanation. Multiple regression analysis showed that language and social life skills were significantly associated with the child's receptive capability, and language and daily life skills were significantly associated with the child's interest and literacy regarding the explanation. Conclusion: Improving children's language, social life, and daily life skills may enhance their receptive capability and literacy regarding explanations of their disease.

• Structural Engineering and Mechanics
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• v.39 no.3
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• pp.339-360
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• 2011

In the h-type adaptive analysis, when an element is refined or subdivided, new nodes are added. Among them are the transition nodes which are the corner nodes of the new elements formed by subdivision and, simultaneously, the mid-side nodes of the adjacent non-subdivided elements. To secure displacement compatibility, the slave-node approach in which the DOFs of a transition node are constrained by those of the adjacent nodes had been used. Alternatively, transition elements which possess the transition nodes as active mid-side/-face nodes can be used. For C0 plate analyses, the conventional slave-node constraints and the previously derived ANS transition elements are implemented. In both implementations, the four-node element is the ANS element. With reference to the predictions of the transition elements, the slave-node approach not only delivers erroneous results but also fails the patch test. In this paper, the patch test failure is resolved by developing a set of new constraints with which the slave-node approach surpasses the transition-element approach. The accuracy of the slave-node approach is further improved by developing a hybrid four-node element in which the assumed moment and shear force modes are in strict equilibrium.

• Journal of Korean Society of Steel Construction
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• v.13 no.5
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• pp.525-533
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• 2001

The wind resistant design of long-span bridges has urged a special attention to the prevention of the flutter occurrence Therefore calculation of flutter derivatives is indispensable to this prediction. A used system identification method must identify all the flutter derivatives from noisy experimental data In this paper MITD(Modified Ibrahim Tim Domain) method and AKF (Adaptive Kalman Filter) method are applied to extract flutter derivatives from section-model tests. The robustness and reliability of proposal SI methods under a high signal-to-noise ratio is demonstrated through numerical simulation for windtunnel test.

• Journal of Astronomy and Space Sciences
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• v.29 no.4
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• pp.389-395
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• 2012

The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.6
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• pp.889-897
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• 1986

The purpose of this study is to describe the strategy of machining process suitable for developing adaptive control with constraint of NC-machine tool. The algorithm that controls machining process parameters of every sampling time is established for the constraint of torque in machinig center. To prove this AC algorithm, manual AC-unit control test is used for simulating the on-line AC strategy control. Also machining tests are carried out on a CNC-machining center fitted with the ACC system and compared with the simulated results. The practical effectiveness of the ACC systems so discussed and the reduction of machining time are demonstrated with reference to typical models of cutting workpieces. As a typical model, taper and step geometry model are selected. The computer simulation results have a good agreement with the experimental observation and make it possible to develope a NC-machine tool with an on-line ACC system.

• Journal of the Korean housing association
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• v.22 no.3
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• pp.113-122
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• 2011

This study aimed to develop AI- (Artificial Intelligence) based thermal control logics and test their performance for identifying the optimal thermal control method in buildings. For this objective, a conventional Two-Position On/Off logic and two AI-based variable logics, which applied ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System), have developed. Performance of each logic was tested in a typical two-story residential building in U.S.A. using the computer simulation incorporating MATLAB and IBPT (International Building Physics Toolbox). In the analysis of the test results, AI-based control logic presented the advanced thermal comfort with stability compared to the conventional logic while they did not show significant energy saving effects. In conclusion, the predictive and adaptive AI-based control logics have a potential to maintain interior air temperature more comfortably, and the findings in this study could be a solid foundation for identifying the optimal thermal control method in buildings.