• 전자공학회논문지
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• 제51권1호
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• pp.202-208
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• 2014

로봇 시스템에 작용하는 마찰력은 비선형 형태이며 특히 저속에서의 정밀 제어를 어렵게 만든다. 본 논문에서는 로봇 연구에서 자주 활용되고 있는 벤치마크 로봇 시스템의 단축 모델에 대한 동적 마찰 보상 문제를 다룬다. 마찰 모델은 동적 특성 및 다양한 효과를 나타낼 수 있도록 비선형 동적 모델인 LuGre 모델을 고려한다. 본 논문에서 제안하는 제어기는 두 부분으로 구성된다. 동적 마찰의 추정 및 보상을 위해 Dual 관측기 기반의 적응 제어기를 사용한다. 마찰 추정 오차 및 나머지 외란을 보상하기 위해 PI 관측기를 추가로 설계한다. 모의실험을 통해 비선형 동적 마찰이 벤치마크 로봇 시스템의 제어 성능에 미치는 영향을 확인하고 제안된 제어기를 사용함으로써 동적 마찰에 대한 제어 성능이 향상됨을 보인다.

• 대한산업공학회지
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• 제37권4호
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• pp.331-341
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• 2011

This paper considers an inbound lot-sizing and outbound dispatching problem for a single product in a thirdparty logistics (3PL) distribution center. Demands are dynamic and finite over the discrete time horizon, and moreover, each demand has a delivery time window which is the time interval with the dates between the earliest and the latest delivery dates All the product amounts must be delivered to the customer in the time window. Ordered products are shipped by multiple vehicle types and the freight cost is proportional to the vehicle-types and the number of vehicles used. First, we formulate a mixed integer programming model. Since it is difficult to solve the model as the size of real problem being very large, we design a conventional genetic algorithm with a local search heuristic (HGA) and an improved genetic algorithm called adaptive genetic algorithm (AGA). AGA spontaneously adjusts crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with HGA.

• 한국정밀공학회지
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• 제25권12호
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• 제어로봇시스템학회논문지
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• 제14권11호
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• pp.1103-1109
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• 2008

Since the flexible joint robots with motor dynamics are represented by the fifth-order nonlinear sγstem, it is difficult and complex to design the controller for electrically driven flexible-joint (EDFJ) robots. In this paper, we propose a simple adaptive control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. For the simple control design, the dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. It is proved that all signals in the controlled closed-loop system are uniformly ultimately bounded. Simulation results for three-link EDFJ manipulators are provided to validate the effectiveness of the proposed control system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2861-2880
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• 2018

Mobile Ad hoc Networks (MANETs) have become a viable platform owing to their potential of providing communication without any pre-existing infrastructure and central administrating authority. Mutual support and co-operation among nodes are prerequisites for performing functions in such networks. The scarcity of resources makes it economical for nodes to conserve their resources and misbehave by avoiding participation in the network. Therefore, a mechanism is required to detect and handle such misbehaving nodes and promote co-operation in the network. Existing techniques for handling misbehaving nodes focus only on their current behaviour without considering the antecedent behaviour of nodes. In real world, a node may dynamically change its behaviour in accordance to its requirements. Hence, an efficient mechanism is required for providing security against such misbehaviour. This paper proposes an Adaptive Security Model which contemplates the present as well as anterior behaviour of nodes for providing security against dynamic node behaviour. The adaptivity of the model is nested in its ability to requite well-behaving nodes and penalize misbehaving ones in conformity with their overall behaviour. Simulation results indicate the efficiency of proposed scheme in securing the network from the menace of dynamic behaviour of nodes.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.372-378
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• 2015

Background subtraction is the first processing stage in video surveillance. It is a general term for a process which aims to separate foreground objects from a background. The goal is to construct and maintain a statistical representation of the scene that the camera sees. The output of background subtraction will be an input to a higher-level process. Background subtraction under dynamic environment in the video sequences is one such complex task. It is an important research topic in image analysis and computer vision domains. This work deals background modeling based on modified adaptive Gaussian mixture model (GMM) with three temporal differencing (TTD) method in dynamic environment. The results of background subtraction on several sequences in various testing environments show that the proposed method is efficient and robust for the dynamic environment and achieves good accuracy.

• 대한원격탐사학회지
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• 제26권6호
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• 대한기계학회논문집A
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• 제24권7호
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• pp.1689-1696
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• 2000

This paper proposes a new adaptive control scheme for flexible-link robots. A model-based nonlinear control scheme is designed based on a V-shape Lyapunov function, and then the nonlinear control i s extended to a model-based adaptive control to cope with parametric uncertainties in the dynamic model. The proposed control guarantees the global exponential or global asymptotic stability of the overall control system with all internal signals bounded. The effectiveness of the proposed control is shown by computer simulation.

• Journal of Electrical Engineering and Technology
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• 제2권4호
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• pp.543-548
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• 2007

We present a dynamic Bayesian network (DBN) model of a generalized class of nonstationary birth-death processes. The model includes birth and death rate parameters that are randomly selected from a known discrete set of values. We present an on-line algorithm to obtain optimal estimates of the parameters. We provide a simulation of real-time characterization of load traffic estimation using our DBN approach.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.208.2-212
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• 1997

In a model based friction comensation for a frictional system,the performance of the system is inflenceed by the selection of the friction model. Especially, when a real plant have dynamic friction characteritics, the compensation of friction with a static friction model may deteriorate the perfomance. For the system we constlucted an adaptiv parameter estimation and friction compensation with a newly introduced dynamic friction model proposed by Canudas et.[1]. The model depicts varios frictional phenomena,such as Stibeck effect,frictional memory, Stick-slip motion. Parmeter identification algorithm are followed conventional RLSM adaptive rule. The stability for the closed system was proved by the Lyapunov stability. The result say that if a real system have dynamic friction property,the friction compensation with the dynamic friction model will improve the perfomance moreover static friction model based compensation may lead to the system unstable.