• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.73-86
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• 2008

Because of its capability of automatic identification of objects, RFID(Radio Frequency Identification) technologies have extended their application areas to logistics, healthcare, and food management system. Load balancing is a basic technique for improving scalability of systems by moving loads of overloaded middlewares to under loaded ones. Adaptive load balancing has been known to be effective for distributed systems of a large load variance under unpredictable situations. There are needs for applying load balancing to RFID middlewares because they must efficiently treat vast numbers of RFID tags which are collected from multiple RFID readers. Because there can be a large amount of variance in loads of RFID middlewares which are difficult to predict, it is desirable to consider adaptive load balancing approach for RFID middlewares, which can dynamically choose a proper load balancing strategy depending on the current load. This paper proposes an adaptive load balancing approach for RFID middlewares and presents its design and implementation. First we decide a performance model by a experiment with a real RFID middleware. Then, a set of proper load balancing strategies for high/medium/low system loads is determined from a simulation of various load balancing strategies based on the performance model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.922-928
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• 2007

This paper presents the fast adaptive algorithm which applies an approximation scheme into RLS algorithm. The proposed algorithm(D-RLS) derives a QRD RLS algorithm derivation process from RLS algorithm recursively. D-RLS has the similar pattern as the algorithm having the approximation that input signals are separated respectively. Computational complexity of D-RLS is O(N), fewer than $O(N^2)$. To evaluate performance of proposed algorithm, we use the system identification method of FIR and Volterra system. And, finally, we can show D-RLS has an excellent performance.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.333-348
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• 2013

Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately $91.33{\pm}0.67%$ for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1139-1158
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• 2015

This paper proposes an efficient system identification method for modeling nonlinear behavior of civil structures. This method is developed by integrating three different methodologies: principal component analysis (PCA), artificial neural networks, and fuzzy logic theory, hence named PANFIS (PCA-based adaptive neuro-fuzzy inference system). To evaluate this model, a 3-story building equipped with a magnetorheological (MR) damper subjected to a variety of earthquakes is investigated. To train the input-output function of the PANFIS model, an artificial earthquake is generated that contains a variety of characteristics of recorded earthquakes. The trained model is also validated using the1940 El-Centro, Kobe, Northridge, and Hachinohe earthquakes. The adaptive neuro-fuzzy inference system (ANFIS) is used as a baseline. It is demonstrated from the training and validation processes that the proposed PANFIS model is effective in modeling complex behavior of the smart building. It is also shown that the proposed PANFIS produces similar performance with the benchmark ANFIS model with significant reduction of computational loads.

• 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 the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.487-492
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method is composed of neural network of state space model type, performs for a unknown nonlinear system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.753-758
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• 1987

The purpose of ocean thermal energy conversion (OTEC) plant control is to provide stable power efficiently by appropriately regulating the seawater flow rates and the working fluid flow rate under conditions of continually changing seawater temperatures. This paper describes digital control of working fluid flow rate based on an adaptive control theory for the "Imari 2" OTEC plant at Saga University. Provisions have been made for linkage between the software of the adaptive control theory and the hardware of the OTEC plant. In implementing the working fluid flow rate control, if persistency of excitation conditions are lost, the algorithm of identification often exhibits bursting phenomena. To avoid this difficulty, the stopping-and-starting rule for identification was derived and was used for the working fluid flow rate control. Satisfactory control performance was then obtained by using this digital control system.ol system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.966-971
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• 2010

An adaptive state observer is presented for a class of LTI systems that have a sinusoidal disturbance in the measurement output. Adaptation rules are developed for identifying the unknown sinusoidal disturbance signal from the system output. For the application of the identification result to the state estimation problem, the sinusoidal signal with arbitrary initial phase has been considered in this paper. In order to test the performance of proposed algorithm, comparative computer simulations have been carried out with an existing robust observer. The simulation results show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.220-227
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• 1999

The position control accuracy of a robot arm is significantly deteriorated when a long slender arm robot is operated at a high speed. In this case, the robot arm needs to be modeled as a flexible structure, not a rigid one, and its control system needs to be designed with its elastic modes taken into account. In this paper, the vibration control scheme of a one-link flexible manipulator using adaptive input shaper in conjunction with PID controller is presented. The robot consists of a flexible arm manufactured with a thin aluminium plate, an AC servo motor with a harmonic drive for speed reduction, an optical encoder and an accelerometer. On-line identification of the vibration mode is done using the pruned decimation-in-time FFT algorithm to estimate the parameter of the input shaper. Experimental results of the flexible manipulator with a PID controller and input shaper are provided to show the effectiveness of the advocated controllers.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.69-72
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• 1987

General schemes for the adaptive control and identification of multivariable systems by model reference approach are developed. Lyapunov's direct method and LaSalle's theorem are employed to ensure the stability of these schemes. An added feature is the simplicity of the stable adaptive laws, which depend explicitly on the state variables of plant and model, and on the plant input. Computer simulation results of several examples illustrate the the effectiveness of the proposed schemes.