• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.416-421
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• 2008

Self-adaptive 시스템에서 adaptation은 시스템 운영의 부담으로 작용할 수 있다. Self-adaptive system의 구조적인 고려는 이러한 부담을 줄일 수 있는 방안의 힌트로써 작용 할 수 있다. 본 논문에서는 self-adaptive 시스템을 구성할 때 가능한 소프트웨어 구조인 사용자 레벨 adaptation과 커널 레벨 adaptation을 살펴보고 각 구조에서 대상에 대한 adaptation을 수행할 때 발생하는 상호작용에 따른 비용을 추정하여 비교하였다. 특히 빠른 적응과 다양한 변화에 따른 적응이 요구되는 Networked Embedded Self-adaptive system을 대상으로 하였다. 본 논문은 Self-adaptive S/W 시스템을 설계할 때 기존의 기능적인 고려 외에 구조적인 고려가 필요함을 말하고자 하며 본 논문의 분석 결과는 Selfadaptive 시스템을 설계하고자 할 때 좋은 참고 자료가 될 수 있을 것이다.

• ETRI Journal
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• v.28 no.6
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• pp.697-708
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• 2006

Various adaptive mesh refinement techniques are often employed in numerical simulations for increasing spatial and temporal resolution beyond the limits imposed by available CPU time and memory space. Recently, an octree-based adaptive mesh structure was successfully used in fluid animation to place more grid cells efficiently in visually interesting regions of fluids. In an attempt to optimize the use of computational resources further in fluid animation, this paper extends this adaptive technique by modifying the mesh refinement scheme so that the camera's viewing properties are dynamically exploited during the simulation. Based on a simple adaptive mesh structure, we show that the new meshing strategy can save a substantial amount of computation time and memory space by using a view-dependent adaptive approach. The experimental results reveal that the proposed technique provides a good compromise between the computational effort and the simulation's fidelity, and may be used quite effectively in 3D animation production.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.261-269
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• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• Journal of Navigation and Port Research
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• v.30 no.2
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• pp.119-124
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• 2006

In Part I(theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot and automatic selection algorithm for learning rate and number of iterations, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.23-28
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• 2005

In Part I (theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.370-372
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• 1994

In this paper, a stable adaptive composite control system consisting of a PID and a fuzzy controllers is designed to control nonlinear systems. In the fuzzy controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. Also, parameters of PID controller change according to some adaptive law. These adaptive laws are based on the Lyapunov synthesis approach. Then, it is proved that the closed-loop system using such an adaptive composite control system is globally stable in the sense that all signals involved are bounded and the tracking error converges to zero. We apply this adaptive composite control system to control a nonlinear system.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.838-846
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• 2006

The purpose of this study to develop the air-conditioning system that adopts adaptive model as an indoor climate control logic for energy saving. The adaptive model using the ability of human thermal adaptation could be expected to alleviate the indoor set-point temperature compared with the past heat-balance model. Especially, in case of hybrid air-conditioning system coupled with natural ventilation and heating/cooling system, the adaptive model can be describe the thermal comfort of inhabitant who stay at hybrid system controlled buildings with accuracy. In this paper, the concept of adaptive model will be described and the results of a continuous measurement on the actual thermal experiences and behaviors of thermal adaptation for office worker will be reported.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.100-104
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• 1998

This paper describes the real-time implementation of an adaptive controller fur the robotic manipulator. Digital signal processors(DSPs) are special purpose micro-processors that are particularly powerful for intensive numerical computations involving sums and products of variables. TMS320C50 chips are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the direct adaptive control theory. The adaptive controller consists of an adaptive feedforward controller and feedback controller. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a assembling robot.