• Title/Summary/Keyword: 선형 근사화

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On a Design of the Nonlinear Direct Adaptive Controller Using Neural Networks (신경망을 이용한 비선형 직접적응제어기 설계에 관한 연구)

  • 이순영;김관수
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.2
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    • pp.109-114
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    • 2001
  • 본 논문에서는 비선형 제어시스템의 성능 개선을 위한 새로운 신경망 직접 적응제어 알고리즘을 제시하였다. 제어칙은 Gaussian RBF 신경망을 이용한 제어입력과 근사화 오차 및 외란의 영향을 제거하기 위한 보조제어 입력으로 구성하였다. 또한 신경망에 사용된 가중치와 보조입력의 파라미터를 조정하기 위한 적응칙은 Lyapunov 안정도 이론에 의하여 구하였다. 이렇게 함으로써 외란이나 근사화 오차에 관계없이 플랜트와 기준모델 사이의 오차가 0이 되도록 하는 알고리즘을 구할 수 있었다. 또한 제시된 알고리즘의 효용성을 알아보기 위하여 Duffing forced oscillation 시스템에 대하여 시뮬레이션 하여본 결과 만족할만한 성능을 얻을 수 있었다.

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Uncertainty-Compensating Neural Network Control for Nonlinear Systems (비선형 시스템의 불확실성을 보상하는 신경회로망 제어)

  • Cho, Hyun-Seob
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.5
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    • pp.1597-1600
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    • 2010
  • In this paper, a direct controller for nonlinear plants using a neural network is presented. The composed of the control input by using RBF neural networks and auxiliary input to compensate for effects of the approximation errors and disturbances. In the results, using this scheme, the output tracking error between the plant and the reference model can asymptotically converge to zero in the presence of bounded disturbances and approximation errors. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

The wavelet neural network using fuzzy concept for the nonlinear function learning approximation (비선형 함수 학습 근사화를 위한 퍼지 개념을 이용한 웨이브렛 신경망)

  • Byun, Oh-Sung;Moon, Sung-Ryong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.5
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    • pp.397-404
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    • 2002
  • In this paper, it is proposed wavelet neural network using the fuzzy concept with the fuzzy and the multi-resolution analysis(MRA) of wavelet transform. Also, it wishes to improve any nonlinear function learning approximation using this system. Here, the fuzzy concept is used the bell type fuzzy membership function. And the composition of wavelet has a unit size. It is used the backpropagation algorithm for learning of wavelet neural network using the fuzzy concept. It is used the multi-resolution analysis of wavelet transform, the bell type fuzzy membership function and the backpropagation algorithm for learning. This structure is confirmed to be improved approximation performance than the conventional algorithms from one dimension and two dimensions function through simulation.

Fractal Image Coding by Linear Transformation of Computed Tomography (전산화단층촬영의 선형변환에 의한 프랙탈 영상 부호화)

  • Park, Jae-Hong;Park, Cheol-Woo
    • Journal of the Korean Society of Radiology
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    • v.11 no.4
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    • pp.241-246
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    • 2017
  • The existing fractal compression method is effective in generating an artificial shape by approximating its partial regions to a domain block by re-dividing the whole image into a domain region and dividing it into several domain blocks, but it is difficult to implement a computer. In this study, it is difficult to approximate a complex block such as a large-sized block and an affine transformation because a large amount of calculation is required in searching for a combination of similar blocks through a transformation, so a large amount of coding time is required.

The Petrov-Galerkin Natural Element Method : III. Geometrically Nonlinear Analysis (페트로프-갤러킨 자연요소법 : III. 기하학적 비선형 해석)

  • Cho, Jin-Rae;Lee, Hong-Woo
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.18 no.2
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    • pp.123-131
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    • 2005
  • According to ow previous study, we confirmed That the Petrov-Galerkin natural element method(PG-NEM) completely resolves the numerical integration inaccuracy in the conventional Bubnov-Galerkin natural element method(BG-NEM). This paper is an extension of PG-NEM to two-dimensional geometrically nonlinear problem. For the analysis, a linearized total Lagrangian formulation is approximated with the PS-NEM. At every load step, the grid points ate updated and the shape functions are reproduced from the relocated nodal distribution. This process enables the PG-NEM to provide more accurate and robust approximations. The representative numerical experiments performed by the test Fortran program, and the numerical results confirmed that the PG-NEM effectively and accurately approximates The large deformation problem.

Substructuring-based Structural Reanalysis by Multilevel Hybrid Approximation (다단계 혼성근사화에 의한 부구조화 기반 구조 재해석)

  • 황진하;김경일;이학술
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.12 no.3
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    • pp.397-406
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    • 1999
  • A new solution procedure for approximate reanalysis, using the staged hybrid methods with substructuring, is proposed in this study. Displacements are calculated with two step mixed procedures. First step is to introduce the conservative approximation, which is a hybrid form of the linear and reciprocal approximation, as local approximation. In the next step, it is combined with the global approximation by reduced basis approach. Stresses are evaluated from the displacements by matrix transformation. The quality of reanalyzed quantities can be greatly improved through these staged hybrid approximations, specially for large changes in the design. Overall procedures are based on substructuring scheme. Several numerical examples illustrate the validity and effectiveness of the proposed methods.

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Function Approximation Using Cao s Fuzzy System (Cao의 퍼지 시스템을 이용한 함수 근사)

  • 길준민;박대희;박주영
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.3
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    • pp.111-116
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    • 1995
  • 본 논문의 목적은 Cao의 퍼지 추론에 기초한 퍼지 시스템이 Universal Approximator임을 증명함으로써 Cao의 퍼지 시스템을 비선형 모델링 문제에 적용하기 위한 이론적 토대를 제공하는 것이다. 즉 우리는 Cao의 퍼지 논리 시스템을 특별한 형태로 수식화하고 수식화된 Cao의 퍼지는 논리 시스템이 임의의 비선형 함수를 충분히 정확하게 근사할 수 있다는 것을 보인다. 이와 같이 증명된 이론은 Cao의 퍼지 시스템이 실제의 공학적 문제에 어떻게 성공적으로 적용되었는지를 설명할 수 있다.

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Development of Direct Optimization Algorithms using Radial Basis Functions (방사상 기본 함수를 사용한 직접최적화 알고리즘에 관한 연구)

  • Hyeon Cheol Gong
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.5
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    • pp.600-607
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    • 1998
  • 일반적인 비선형 동역학 최적화문제를 비선형 프로그래밍 문제로 변환하는데 제어변수들을 방사성 기본 함수로 근사화하는 방법이 사용되었다. 방사성 기본 함수의 계수들을 연속적으로 보정하기 위하여 최소수정기법에 기초를 둔 비선형 프로그래밍 알고리즘이 연구되었다. 이러한 알고리즘을 실제적인 다변수 제어 시스템에 적용하여 성능을 검증하였다.

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Approximate SHE PWM for Real-Time Control of 2-Level Inverter (3레벨 인버터의 실시간 제어를 위한 근사화 SHE PWM)

  • 박영진;홍순찬
    • The Transactions of the Korean Institute of Power Electronics
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    • v.3 no.4
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    • pp.365-374
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    • 1998
  • The SHE(Selected Harmonic Elimination) PWM scheme which eliminates specific lower order harmonics can generate h high quality output waveforms in 3-level PWM inverters. However. its application has limited since SHE switching a angles cannot be calculated on-line by a microprocessor-implemented control system. Based on off-line optimization. in which multiple SHE solutions were found and analysed for 2 to 5 switching angles per quarter in the 3-level SHE PWM pattern. this paper presents an algebraic algorithm for an ordinary microprocessor to calculate approximate SHE S switching angles on-line with such high resolution that it makes no practical difference between the accurate and the a approximate SHE switching angles. By employing the variable of the dc-link voltage Vdc' the proposed SHE PWM p pattern can ideally compensate the dc input fluctuation together with selected harmonics eliminated.

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