• 제목/요약/키워드: Surface Adaptive

검색결과 394건 처리시간 0.03초

조립용 로봇의 가변구조 적응제어 (Variable Structure Adaptive Control of Assembling Robot)

  • 한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1997년도 춘계학술대회 논문집
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    • pp.131-136
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    • 1997
  • This paper represent the variable structure adaptive mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in contiuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. the sampling process often forces the trajectory to oscillate in the neighborhood of the sliding surface. Adaptive control technique is particularly well-suited to robot manipulators where dynamic model is highly complex and may contain unknown parameters. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple sturcture is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control, Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

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Adaptive Contrast Stretching for Land Observation in Cloudy Low Resolution Satellite Imagery

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • 대한원격탐사학회지
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    • 제28권3호
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    • pp.287-296
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    • 2012
  • Although low spatial resolution satellite images like MODIS and GOCI can be important to observe land surface, it is often difficult to visually interpret the imagery because of the low contrast by prevailing cloud covers. We proposed a simple and adaptive stretching algorithm to enhance image contrast over land areas in cloudy images. The proposed method is basically a linear algorithm that stretches only non-cloud pixels. The adaptive linear stretch method uses two values: the low limit (L) from image statistics and upper limit (U) from low boundary value of cloud pixels. The cloud pixel value was automatically determined by pre-developed empirical function for each spectral band. We used MODIS and GOCI images having various types of cloud distributions and coverage. The adaptive contrast stretching method was evaluated by both visual interpretation and statistical distribution of displayed brightness values.

비정합 불확실성을 갖는 시스템을 위한 적응 슬라이딩 모드 제어기 설계 (Adaptive Sliding Mode Control Design for Mismatched Uncertain Systems)

  • 최한호
    • 조명전기설비학회논문지
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    • 제24권2호
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    • pp.39-43
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    • 2010
  • 본 논문에서는 불확실한 다변수 시스템을 위한 적응 슬라이딩 모드 제어기의 LMI 기반 설계방법이 제시된다. LMI를 사용하여 슬라이딩 평면의 존재조건을 구한다. 그리고 외란의 놈 경계치를 추정하고 안정성을 보장할 적응 스위칭 궤환 제어기 알고리즘을 제시한다. 마지막으로 제안된 방법의 유효성을 보이기 위해 크레인 모델을 제어하기 위한 설계 예를 제시한다.

Adaptive B-spline volume representation of measured BRDF data for photorealistic rendering

  • Park, Hyungjun;Lee, Joo-Haeng
    • Journal of Computational Design and Engineering
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    • 제2권1호
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    • pp.1-15
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    • 2015
  • Measured bidirectional reflectance distribution function (BRDF) data have been used to represent complex interaction between lights and surface materials for photorealistic rendering. However, their massive size makes it hard to adopt them in practical rendering applications. In this paper, we propose an adaptive method for B-spline volume representation of measured BRDF data. It basically performs approximate B-spline volume lofting, which decomposes the problem into three sub-problems of multiple B-spline curve fitting along u-, v-, and w-parametric directions. Especially, it makes the efficient use of knots in the multiple B-spline curve fitting and thereby accomplishes adaptive knot placement along each parametric direction of a resulting B-spline volume. The proposed method is quite useful to realize efficient data reduction while smoothing out the noises and keeping the overall features of BRDF data well. By applying the B-spline volume models of real materials for rendering, we show that the B-spline volume models are effective in preserving the features of material appearance and are suitable for representing BRDF data.

Design of Reconfigurable Flight Controller Using Discrete Model Reference Adaptive Scheme

  • Hyung, Seung-Yong;Kim, You-Dan
    • International Journal of Aeronautical and Space Sciences
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    • 제8권1호
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    • pp.79-86
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    • 2007
  • In this paper, an adaptive control algorithm using system identification is proposed for an aircraft fault tolerant control system. A discrete state-space system is reformulated to be the ARX model which has the advantage in handing variable structure systems. Discrete model reference adaptive control is used to make the output of fault system follow the output of reference model. To validate the performance of the proposed control scheme, numerical simulations are performed for the high performance aircraft with control surface damage.

유사 색상 영역의 적응적인 주성분 분석을 이용한 표면분광반사율 추정 (Spectral-Reflectance Estimation Using Adaptive Principle Component Analysis in Similar Color Region)

  • 권오설;이철희;이호근;하영호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.1767-1770
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    • 2003
  • This paper proposes an algorithm that can reduce the estimation error of surface spectral-reflectance(SR) when using a conventional 3-band RGB camera. In the proposed method, the estimation error is reduced by using adaptive principle components (PCs) for each color region. To build an adaptive set of PCs, n SR populations are organized for n PC sets using the Lloyd quantizer design algorithm. The Macbeth Color Checker is utilized for the initial representative SR values for 1485 Munsell color chips as the total color population, then the Munsell chips arc divided into subsets with a set of corresponding adaptive PCs organized for each subset.

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Modified adaptive complementary sliding mode control for the longitudinal motion stabilization of the fully-submerged hydrofoil craft

  • Liu, Sheng;Niu, Hongmin;Zhang, Lanyong;Xu, Changkui
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제11권1호
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    • pp.584-596
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    • 2019
  • This paper presents a Modified Adaptive Complementary Sliding Mode Control (MACSMC) system for the longitudinal motion control of the Fully-Submerged Hydrofoil Craft (FSHC) in the presence of time varying disturbance and uncertain perturbations. The nonlinear disturbance observer is designed with less conservatism that only boundedness of the derivative of the disturbance is required. Then, a complementary sliding mode control system combined with adaptive law is designed to reduce the bound of stabilization error with fast convergence. In particularly, the modified complementary sliding mode surface which contains the estimation of the disturbance can reduce the switching gain and retain the normal performance of the system. Moreover, a hyperbolic tangent function contained in the control law is utilized to attenuate the chattering of the actuator. The global asymptotic stability of the closed-loop system is demonstrated utilizing the Lyapunov stability theory. Ultimately, the simulation results show the effectiveness of the proposed approach.

New framework for adaptive and agile honeypots

  • Dowling, Seamus;Schukat, Michael;Barrett, Enda
    • ETRI Journal
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    • 제42권6호
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    • pp.965-975
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    • 2020
  • This paper proposes a new framework for the development and deployment of honeypots for evolving malware threats. As new technological concepts appear and evolve, attack surfaces are exploited. Internet of things significantly increases the attack surface available to malware developers. Previously independent devices are becoming accessible through new hardware and software attack vectors, and the existing taxonomies governing the development and deployment of honeypots are inadequate for evolving malicious programs and their variants. Malware-propagation and compromise methods are highly automated and repetitious. These automated and repetitive characteristics can be exploited by using embedded reinforcement learning within a honeypot. A honeypot for automated and repetitive malware (HARM) can be adaptive so that the best responses may be learnt during its interaction with attack sequences. HARM deployments can be agile through periodic policy evaluation to optimize redeployment. The necessary enhancements for adaptive, agile honeypots require a new development and deployment framework.

Adaptive Sliding Mode Control을 이용한 전기유압식 서어보시스템의 위치제어에 관한 연구 (A Study on the Position Control of Electrohydraulic Servo System Using Adaptive Sliding Mode Control)

  • 현장환;이정오
    • 한국정밀공학회지
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    • 제11권6호
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    • pp.143-157
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    • 1994
  • This paper is concerned with the position control of electrohydraulic servo system under parameter variation. An adaptive sliding mode control which uses the direct parameter estimation scheme, is proposed to design a robust controller for fast and accurate control of the system. It is shown that the adaptive sliding mode control algorithm is robust and effective in attaining fast and accurate position control of system under time-dependent parameter variation. It is also shown experimentally that chattering phenomena in a sliding mode control can significantly be reduced by using boundary layer technique, and that new approach in sliding mode control introducing a term proportional to the distance between the current state and the sliding surface in the control law is effective to obtain fast response and to increase stability of the system. Computer simulation on the dynamic performance of the control system is also presented.

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주성분 분석을 활용한 적응형 근전도 패턴 인식 알고리즘 (Adaptive sEMG Pattern Recognition Algorithm using Principal Component Analysis)

  • 김세진;정완균
    • 로봇학회논문지
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    • 제19권3호
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    • pp.254-265
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    • 2024
  • Pattern recognition for surface electromyogram (sEMG) suffers from its nonstationary and stochastic property. Although it can be relieved by acquiring new training data, it is not only time-consuming and burdensome process but also hard to set the standard when the data acquisition should be held. Therefore, we propose an adaptive sEMG pattern recognition algorithm using principal component analysis. The proposed algorithm finds the relationship between sEMG channels and extracts the optimal principal component. Based on the relative distance, the proposed algorithm determines whether to update the existing patterns or to register the new pattern. From the experimental result, it is shown that multiple patterns are generated from the sEMG data stream and they are highly related to the motion. Furthermore, the proposed algorithm has shown higher classification accuracy than k-nearest neighbor (k-NN) and support vector machine (SVM). We expect that the proposed algorithm is utilized for adaptive and long-lasting pattern recognition.