• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.483-488
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• 1989

In this paper, the concept of persistent excitation(PE) is examed and the model reference adaptive control of a linear plant subjected to bounded disturbances is considered. Computer simulation reasults of nonlinear differential equations shows that the global behavior of the adaptive system depends upon the PE of the reference input as well as the amplitude of the external disturbances. The sufficient conditions on the PE of the reference input for the signals in the adaptive system to be globally bounded has been derived.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.603-608
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• 2006

As an important and relatively easy to implement technology for realizing Intelligent Transportation Systems(ITS), Adaptive Cruise Control(ACC) automatically adjusts vehicle speed and distance to a preceding vehicle, thus enhancing driver comfort and safety. One of the key issues associated with ACC development is usability and user acceptance. Control parameters in ACC should be optimized in such a way that the system does not conflict with driving behavior of the driver and further that the driver feels comfortable with ACC. A driving simulator is a comprehensive research tool that can be applied to various human factor studies and vehicle system development in a safe and controlled environment. This study investigated driving behavior with ACC for drivers with different driving styles using the driving simulator. The ACC simulation system was implemented on the simulator and its performance was evaluated first. The Driving Style Questionnaire(DSQ) was used to classify the driving styles of the drivers in the simulator experiment. The experiment results show that, when driving with ACC, preferred headway-time was 1.5 seconds regardless of the driving styles, implying consistency in driving speed and safe distance. However, the lane keeping ability reduced, showing the larger deviation in vehicle lateral position and larger head and eye movement. It is suggested that integration of ACC and lateral control can enhance driver safety and comfort even further.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3095-3111
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• 2018

Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.344-350
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• 1996

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2050-2058
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• 2001

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of 7he convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Korean Journal of Culture and Social Issue
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• v.15 no.4
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• pp.565-589
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• 2009

The present study explored the major components of adaptive game behavior among adolescents in Korea. Based on relevant research and a pilot testing, an Adaptive Game Use Scale (AGUS) was developed and validated. A stratified sampling procedure was used to draw a representative sample, and a total of 600 male and female students from middle schools and high schools in various regions participated in the study. Factor analyses revealed 7 facets of adaptive game behavior, including experiencing vitality, expanding life experience, making good use of leisure time, experiencing flow, exercising control, experiencing self-esteem, maintaining and expanding social network. Internal consistency and temporal stability(4 weeks) of the scale were both high. A confirmatory factor analysis indicated that a 7-factor hierarchical model fits well with the data. Moreover, additional analyses suggested that AGUS and game addiction are conceptually distinct. Correlational analyses also indicated that AGUS has good discriminant validity and concurrent validity. Implications of the findings and future directions were discussed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.92-103
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• 1993

In this paper, we propose an adaptive classifier based on uncertainty of features for 3D planar object recognition. First, we investigate the uncertainty of depth information and the feature values of 3D planar object by numerical method. And, we observed that the statistical behavior of feature is dependent on the position and orientation of objects. After that, the approximation of the statistical behavior is executed. Subsequently, the recognition procedure is executed by the adaptive classifier. By computer simulation, we confirmed that the proposed classifier is useful for 3D planar object recognition.

• Journal of Venture Innovation
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• v.6 no.2
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• pp.101-121
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• 2023

The purpose of this study was to investigate the impact of issue leadership by sales managers on sales team performance, while examining the mediating role of team adaptive sales behavior and the moderating effect of team-member exchange (TMX). Data was collected from 125 sales teams, and both independent and dependent variables were measured with a time difference of two months using responses from sales managers and team members. The empirical analysis revealed several important findings. Firstly, the study found that issue leadership had a significant positive effect on sales team performance. Secondly, team adaptive sales behavior was found to partially mediate the relationship between issue leadership and sales team performance. Lastly, the study revealed that TMX moderated the relationship between issue leadership and sales team performance. These findings have significant academic and practical implications. Firstly, the study demonstrates the effectiveness of issue leadership as a sales leadership style in the B2C industry. Secondly, it highlights the importance of team adaptive sales behavior as a mechanism that mediates the relationship between issue leadership and sales team performance. Lastly, it underscores the significance of TMX as a situational factor that moderates the relationship between issue leadership and sales team performance. In practice, the results suggest that organizations should focus on developing issue leaders, fostering creative sales behavior at the team level, and activating social exchange within sales teams to enhance sales team performance.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.156-159
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• 1996

An adaptive predictive control for steam-reforming plant which consist of a steam-gas reformer and a waste heat steam-boiler was studied by using MIMO bilinear model. The simulation experiments of the process identification were performed by using linear and bilinear models. From the simulation results it was found that the bilinear model represented the dynamic behavior of a steam-reforming plant very well. ARMA model was used in the process identification and the adaptive predictive control. To verify the performance and effectiveness of the adaptive predictive controller proposed in this study the simulation results of steam-reforming plant control based on bilinear model were compared to those of linear model. The simulation results showed that the adaptive predictive controller based on bilinear model provides better performance than those of linear model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.330-335
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• 1994

In this paper, adaprive control and sliding mode control are combined to implement the proposed adaptive sliding mode control(ASMC) algorithm which is new approach to the control of industrial robot manipulator with external disturbances and parameter uncertainties. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The contribution of this method is that the parameters of the sliding surface are replaced by time varying parameters whose are calculated by an adaptation algorithm, which forces the errors to follow the behavior of a reference error model. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications.