• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.12
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• pp.698-704
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• 2003

Autoreclosure provides a mean of improving power transmitting ability and system stability. The conventional reclosure adopts the fixed dead time interval strategy, that is, the reclosure is activated after a time delay to restore the system to normal as quickly as possible without regard to the system conditions, however, these simple techniques cannot give the optimal operating performance. For this reason, various adaptive reclosure algorithms have been proposed recently, This paper presents an adaptive autoreclosure algorithm including the variable dead time, optimal reclosure, sequential reclosure and emergency extended equal-area criterion (EEAC) algorithm in order to improve the system stability. The reclosure algorithm performs out the operations that are attuned to the power system conditions. The proposed adaptive reclosure algorithm is verified and tested by using EMTP MODELS, and the simulation results show that the system oscillations are reduced and the transient stability is enhanced by employing the proposed adaptive reclosure algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.454-457
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• 1997

As in most industrial processes, the dynamic characteristics of an electric power system are subject to changes. Amongst those effects which cause the system to be uncertain, faults on transmission lines are considered. For the stabilization of the power system, we present an indirect adaptive control method, which is capable of tracking a sudden change in the effective reactance of a transmission line. As the plant dynamics are nonlinear, an input-output feedback linearization method equipped with nonlinear damping terms is combined with an identification algorithm which estimates the effect of a fault. The stability of the resulting adaptive nonlinear system is investigated.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.993-998
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• 1988

Adaptive control system has evolved as an attempt to avoid degradation of the dynamic performance of a control system when environmental variations occurs. While the feedback control system is oriented toward the elimination of the effect of state perturbations, the adaptive control system is oriented toward the elimination of the effect of structural perturbation, upon the performances of the control system. The model reference adaptive controller is utilized in velocity loop controller for positioning and tracking is designed based on the linear decoupled dynamics.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.393-398
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• 2016

Collective Adaptive System is an adaptive multi-agent system which accomplishes its goal by collaborating various agents. Because the collective property of the Collective Adaptive System is accomplished by the goal of the system being based on collaboration, testing the goal accomplishment and their interactions among heterogeneous agents is important. This paper presents a feasibility study of applying a model-based testing approach using task-based test model to a Collective Adaptive System. This paper describes additional information to be applied for Collective Adaptive System for future studies. To analyze our approach, we applied the proposed approach to a smart home system as a case study; our results indicated that we can systematically derive test cases to check whether the Collective Adaptive System successfully achieved its goals by modifying and extending the existing task model.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.177-180
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• 1996

The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.1-162
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• 2001

In this paper, the adaptive fuzzy system is used as an adaptive approximator for robot nonlinear dynamic. A theoretical justification for the adaptive approximator is proving that if the representive point(RP or switching function) and its derivative in sliding mode control are used as the inputs of the adaptive fuzzy system, the adaptive fuzzy system can approximate robot nonlinear dynamics in the neighborhood of the switching surface. Thus the fuzzy controller design is greatly simplified and at the same time, the fuzzy control rule can be obtained easily by the reaching condition. Based on this, a new method for designing an adaptive fuzzy control system based on sliding mode is proposed for the trajectory tracking control of a robot with unknown nonlinear dynamics.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.444-452
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• 2003

An integration system with multi-measurement sets can be realized via combined application of a centralized and federated Kalman filter. It is difficult for the centralized Kalman filter to remove a failed sensor in comparison with the federated Kalman filter. All varieties of Kalman filters monitor innovation sequence (residual) for detection and isolation of a failed sensor. The innovation sequence, which is selected as an indicator of real time estimation error plays an important role in adaptive mechanism design. In this study, the centralized Kalman filter with adaptive measurement fusion is introduced by means of innovation sequence. The objectives of adaptive measurement fusion are automatic isolation and recovery of some sensor failures as well as inherent monitoring capability. The proposed adaptive filter is applied to the GPS/SDINS integration system with an additional sensor. Simulation studies attest that the proposed adaptive scheme is effective for isolation and recovery of immediate sensor failures.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.76-82
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• 2009

A Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear multi-input multi-output (MIMO) system. This system is very difficult to control the temperature and the humidity ratio of a thermal space because of complex nonlinear characteristics. This paper proposes an adaptive fuzzy output feedback control based on observer for the nonlinear HVAC system. The nonlinear HVAC system is linearized through dynamic extension. State observers are designed for estimating state variables of the HVAC system. Fuzzy systems are employed to approximate uncertain nonlinear functions of the HVAC system with unavailable state variables. The obtained controller compares with an adaptive feedback controller. Simulation is given to demonstrate the effectiveness of our proposed adaptive fuzzy method.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.135-139
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• 1992

Control of tool-environment interaction force to comply the robot system to an environment is of vital in many automated process. This paper presents the implementation of an adaptive force control with commercial robot system in two dimensional contour following task. A model reference adaptive control system, combined with the linear compensators, is implemented. That is, a use of adaptive control is to provide an auxiliary control system so that the contour following performance can be improved from that of using linear control system only. Hyperstability is used to derive the adaptive control law. Experimental verification of the proposed control system is obtained using PUMA 560 robot system. Data obtained experimentally shows that the use of additional adaptive control system improves the contour following performance about 30% in RMS contact force errors upon that of the system controlled by the linear compensators only.