• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.108.2-108
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• 2001

This paper presents the application of adaptive phase-locked loop (adaptive PLL) technique to control the process variable of the process control system. The adaptive algorithm is related to the error. When the error of the system is changed, the adaptive gain will be directly changed according to the error. If the value of the adaptive gain is large, the value of the error will be large. In this experiment, the reference input is 50% step input. The experimental result in controlling the first order lag process by the adaptive PLL shows that the response of the controlled system has no overshoot, short rise time, and zero steady-state error. The experimental result also shows that when the output disturbance enters to the process control system, the adaptive PLL can maintain the stability of the system and the effect of the output disturbance can also be fast rejected. The adaptive PLL has better performance ...

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.378-384
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• 1993

In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.5
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• pp.50-56
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• 2010

Meshfree methods show many advantages over finite element method(FEM) in the class of problems for which the remeshing process is inevitable when the conventional FEM used, such as propagating crack problems, large deformation and so on. One of the promising applications of meshfree methods is the adaptive refinement for problems having multi-scale nature. In this study, an adaptive node generation procedure is proposed and several numerical examples are also presented to illustrate the efficiency of proposed method.

• East Asian mathematical journal
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• v.34 no.4
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• pp.451-462
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• 2018

This study analyzed the learning components of the web-based adaptive math learning programs in order to develop adaptive math learning program using artificial intelligence. The components of the web-based adaptive math learning program set for analysis are classified into learning process presentation, concept learning, problem presentation, problem solving process, and learning result processing then analyzed three programs. As a result of analysis, the typical characteristic of components is that it uses a method of repeatedly presenting the same type of problem in order to learn one concept.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.740-745
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• 1988

New design methods for constructing nonlinear adaptive control system are considered. The proposed adaptive controllers are applicable to the case where the degree of the controlled process is unknown. It is shown that the degree of the controller is determined independently of the degree of the process. Several types of nonlinear functions are introduced to deal with uncertainties of the degree of the process. Finally, some simulation results show the effectiveness and simplicity of the proposed methods.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.27-33
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• 1999

In order to regulate cutting force at a desired level during NC lathe process, a feedrate override Adaptive Control Constraint system was developed. Nonlinear model of the cutting process was linearized as an adaptive model with a time varing process parameter. Performance of the ACC system was confirmed on the NC lathe equipped with the developed NC system through a large amount of experiment.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.723-738
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• 2020

In this paper, we study a method to discriminate between trend stationary and difference stationary processes. Since a crucial ingredient of this discrimination is to determine the existence of unit root, we can use a unit root testing strategy. So, we introduce a discrimination based on unit root testing and propose the method using the adaptive lasso. Our Monte Carlo simulation experiments show that the adaptive lasso improves the discrimination accuracy when the process is trend stationary, but has lower accuracy than unit root strategy where the process is difference stationary.

• International Journal of Human Ecology
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• v.15 no.1
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• pp.51-63
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• 2014

Services for self-designing, or adaptive customization services, have become dominant in virtual marketplaces and are believed to create additional values both for the company as well as for the customer. While most research focused on the value from the services' outputs, this research attempts to address the customer-perceived value deriving from the process of the services, and focuses on the self-fulfillment effect of the involved mental processing. An online survey was administered with 313 U.S. shoppers. In the results, participants using adaptive customization services reported higher self-fulfillment perceptions, than did those not using the services. Furthermore, both the self-fulfillment perceptions (i.e., autonomy and competence) significantly increased perceived design utility. The results suggest that the process of adaptive customization services should be strategically managed to improve the customers' positive mental states that subsequently improve the perceived value of the output designs. Implications and suggestions for future studies are dsicussed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.78-89
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• 1991

This Paper presents an application example of the Adaptive Robust Servocontrol (ARSC) scheme, which is an explicit (or indirect) pole-assignment adaptive algorithm with the property of "robustness". The ARSC scheme is applied to an end-milling process for cutting force regulation. It is shown that the federate of an end-milling process can be maximized by the adaptive regulation of the peak cutting force through the ARSC scheme. The results of simulation study and real cutting experiment are presented. It has been verified that asymptotic regulation can be achieved with robustness against the slowly time-varying perturbations to the process model parameters, which are caused by nonlinear cutting dynamics. dynamics.