• 한국정밀공학회지
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• 제29권1호
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• pp.25-32
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• 2012

In this study, we present a gripping mechanism that is inspired by caterpillar's proleg. A caterpillar's proleg has planta that gives compliance to the proleg by greatly deforming its shape. In the bio-inspired gripper, the planta is implemented by flexure joints. The flexures buckle when end force and end moment is applied on the joint in opposite direction. Using this characteristic, the gripping structure is designed so that the flexure buckling can occur. Flexure buckling increases the region where gripping force is constant and this region leads to increasing in gripping range. At the same time, flexure buckling decouples all spines and therefore all spines can move differentially and independently. With this simple but effective mechanism, the bioinspire gripper can achieve adaptive gripping on rough and rugged surfaces. A prototype is built to demonstrate adaptive gripping on rough and rugged surfaces such as cement block, brick.

• Asian-Australasian Journal of Animal Sciences
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• 제20권5호
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• pp.742-747
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• 2007

In order to investigate the mechanism of adaptation to long-term heat stress, six female buffalo calves of about 7 to 8 months age, were exposed to the cool-comfort environment (THI 65) for 21 days to obtain normal values of blood acid-base. An adaptive response of acid-base regulation was determined to long term (21 days) exposure of buffalo calves to hot-dry (THI 80) and hot-humid (THI 84) conditions. Higher rectal temperature and respiratory rate was recorded under hot-humid exposure compared to hot-dry. Significant reduction in the rectal temperature and respiratory rate on day 21 of hot-dry exposure indicated early thermal adaptation compared to hot-humid. Decreasing rectal temperature and respiratory rate from day 1 to 21 was associated with concurrent decrease in blood pH and pCO2. Increased plasma chloride concentration with low base excess in blood and in extracellular fluid suggested compensatory response to respiratory alkalosis. Reduced fractional excretion of sodium with increased fractional excretion of potassium and urine flow rate indicated renal adaptive response to heat stress.

• ETRI Journal
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• 제27권1호
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• pp.43-52
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• 2005

In this paper, we introduce an adaptive radio resource allocation for IP-based mobile satellite services. We also present a synchronous multibeam CDMA satellite system using an orthogonal resource sharing mechanism among downlink beams for the adaptive packet transmission. The simulation results, using a Ka-band mobile satellite channel and various packet scheduling schemes, show that the proposed system and resource allocation scheme improves the beam throughput by more than two times over conventional systems. The simulation results also show that, in multibeam satellite systems, a system-level adaptation to a user's channel and interference conditions according to user locations and current packet traffic is more efficient in terms of throughput improvement than a user-level adaptation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.46-51
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• 2004

This paper presents an adaptive control method based on parameter linearization for incompletely restrained wire-suspended mechanisms. The main purpose of this control method is utilizing it in a walking assist service robot for elderly people. This method is computationally simple and requires neither end-effector acceleration feedback nor inversion of estimated inertia matrix. In the proposed adaptive control law, mass, moment of inertia and external force and torque on the end-effector are considered as components of parameter adaptation vector. Nonlinear simulation for walking an elderly shows the effectiveness of the parameter adaptation law.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.31-36
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• 2008

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• 한국산업융합학회 논문집
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• 제23권2_2호
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• pp.313-321
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• 2020

In this paper, two types of linear actuation methods for the previously proposed adaptive gripper are presented, which includes actual parallelogram inside a five-bar mechanism and has the advantages of smaller actuation torque and larger stroke over the commercial adaptive gripper by RobotiQ. The forward/inverse kinematics and statics analyses for two types of linear actuations are derived. From the inverse kinematics and statics analyses, linear actuation type I is selected and the gripper prototype is designed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.920-924
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• 2005

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the environment. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.570-572
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• 2005

This paper is proposed adaptive hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.143-146
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for speed control of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions.

• Journal of Advanced Marine Engineering and Technology
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• 제28권4호
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• pp.611-617
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• 2004

Pixel classification is one of basic image processing issues. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time. a pixel classification scheme based on image direction measure is proposed. As a typical application instance of pixel classification, an adaptive multi-level median filter is presented. An image can be classified into two types of areas by using the direction information measure, that is. smooth area and edge area. Single direction multi-level median filter is used in smooth area. and multi-direction multi-level median filter is taken in the other type of area. What's more. an adaptive mechanism is proposed to adjust the type of the filters and the size of filter window. As a result. we get a better trade-off between preserving details and noise filtering.