• 제목/요약/키워드: adaptive linear structure

검색결과 107건 처리시간 0.041초

비최소 위상 확률 시스템을 대상으로 한 견실한 적응 IMC 제어기 (Robust adaptive IMC controller for a class of nonminimum phase stochastic systems)

  • 최종호;김호찬
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.139-144
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    • 1993
  • In this paper, a robust reduced order adaptive controller is proposed based on Internal Model Control(IMC) structure for stochastic linear stable systems. The concept of gain margin is utilized to make the adaptive IMC controller robust. We prove the stability of the proposed adaptive IMC system for stable plants under the assumption that upper bounds for system orders are known. Simulation results show that the proposed method has good performance and stability robustness.

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선형 제한 조건을 갖는 적응 Escalator 빔 형성기 (An Adaptive Escalator Beamformer with Linear Constraints)

  • 김희창;김기만;박상택;차일환;윤대희
    • 전자공학회논문지B
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    • 제30B권8호
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    • pp.16-22
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    • 1993
  • As a method of separating the signal arriving from a desired direction in the presence of noise and interfering signals, a linearly constrained adaptive beamformer based on the escalator (Gram-Schmidt) structure is presented. The weights are chosen to minimize local output power subject to the response constraint. The performances of the proposed escalator adaptive beamformer are compared with those of cascade adaptive beamformer via computer simulations.

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A Nonlinear Transformation Approach to Adaptive Output Feedback Control of Uncertain Nonlinear Systems

  • Ahn, Choon-Ki;Kim, Beom-Soo;Lim, Myo-Taeg
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.48.1-48
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    • 2001
  • In this paper, we present a global adaptive output feedback control scheme for a class of uncertain nonlinear systems to which adaptive observer backstepping method may not be applicable directly. The allowed output feedback structure includes quadratic and multiplicative dependency of unmeasured states. Our novel design technique employs a change of coordinates and adaptive backstepping. With these proposed tools, we can remove linear and quadratic dependence on the unmeasured states in the state equation. Also, the multiplication of the two unmeasured states can be eliminated ...

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Adaptive-Linear-Neuron 구조의 ANN을 이용한 3상 PWM 컨버터의 개방고장 진단 (Open Fault Diagnosis Using ANN of Adaptive-Linear-Neuron Structure for Three-Phase PWM Converter)

  • 김원재;김상훈
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2019년도 추계학술대회
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    • pp.136-137
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    • 2019
  • 본 논문에서는 ADALINE (Adaptive-Linear-Neuron) 구조의 ANN(Artificial Neural Network)을 이용한 3상 PWM 컨버터의 개방고장 진단 방법에 대해 제안한다. 3상 PMW 컨버터에서 스위치의 개방고장이 발생한 경우 보호회로에 의해 시스템이 중단되지 않으며, 개방고장으로 인한 상전류의 고조파와 직류 성분에 의해 주변 기기에 고장에 의한 파급효과가 나타날 수 있다. 이에 본 논문에서는 ADALINE을 이용하여 각 상의 THD(Total Harmonics Distortion)와 직류 성분 얻고 대소비교를 통해 개방고장이 발생한 스위치를 진단하는 방법에 대해 제안한다.

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초안정도 방법에 의한 안정한 시연속 기준모델 적응제어기의 설계 (A Design of Stable Continuous-time Model Reference Adaptive Controllers by a Hyperstability Method)

  • 이호진;정종대;최계근
    • 대한전자공학회논문지
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    • 제26권10호
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    • pp.1488-1497
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    • 1989
  • In this paper, a new adaptive control scheme is proposed that uses a special form of rational function-type linear operator in the parameter adaptation and that removes the augmenting signal terms of the control input components. This adaptation scheme is applied to the MRAC of continuous-time, linear time-invariant, minimum-phase plants whose relative degrees are arbitrary. This scheme can be applied without any change of the controller structure to the adaptive systems regardless of the relative degree if it is greater than 1. And this scheme does not require any signal augmentation for arbitrary relative-degree plants if the reference model has no zeros. The asymptotic stability of the adaptive systems controlled by this scheme is shown by a hyper-stability method.

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적응 쌍선형 격자필터(I) - 쌍선형 격자구조 (Adaptive Bilinear Lattice Filter(I)-Bilinear Lattice Structure)

  • Heung Ki Baik
    • 전자공학회논문지B
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    • 제29B권1호
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    • pp.26-33
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    • 1992
  • This paper presents lattice structure of bilinear filter and the conversion equations from lattice parameters to direct-form parameters. Billnear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients required. The lattice filter formulation transforms the nonlinear filtering problem into an equivalent multichannel linear filtering problem and then uses multichannel lattice filtering algorithms to solve the nonlinear filtering problem. The lattice filters perform a Gram-Schmidt orthogonalization of the input data and have very good easily extended to more general nonlinear output feedback structures.

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가변 구조를 갖는 적응 제어기의 설계에 관한 연구 (A Study on the Design of an Adaptive Controller with Variable Structure)

  • 홍연찬;최종헌
    • 전자공학회논문지B
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    • 제33B권1호
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    • pp.1-5
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    • 1996
  • 고전적인 선형 제어와 가변 구조 제어를 융합한 방식에서 가상 공정(nominal plant)을 적응 관측기로 대체하여 실제 공정의 출력과 가상 공정의 출력 간의 오차가 계속 잔존하게 되는 문제를 해결하였다. 적응 관측기로서는 지수 함수적으로 수렴하는 적응 관측기를 사용하였으므로, 실제 공정의 출력에 적응 관측기의 출력이 빠르게 수렴하여 오차가 잔존하지 않게 되어 제어 시스템의 성능이 저하되는 것을 방지할 수 있다.

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적응 신호 처리를 위한 고속 선형 위상 FIR 필터 (Fast linear-phase FIR filter for adaptive signal processing)

  • 최승진;이철희;양홍석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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    • pp.172-177
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    • 1988
  • In this paper, a new fast algorithm of FIR least squares filter with linear phase is presented. The general unknown statistics case is considered, whereby only sample records of the data are available. Taking advantage of the near-to-Toeplitz+Hankel structure of the resulting normal equation, a fast algorithm which gurantees the linear phase constraint, is developed that recursively produces the filter coefficient of linear phase FIR filter for a single block of data.

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Active Random Noise Control using Adaptive Learning Rate Neural Networks

  • Sasaki, Minoru;Kuribayashi, Takumi;Ito, Satoshi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.941-946
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    • 2005
  • In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

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직접법에 의한 이산시간 기준모델 적응제어 시스템 설계에 관한 연구 (A Design of Discrete-Time Model Reference Adaptive Control System by Direct Method)

  • 김성덕
    • 한국통신학회논문지
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    • 제10권5호
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    • pp.258-265
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    • 1985
  • 이 論文은 SISO 離散時間 基準모델 適應制御시스템에 대한 設計問題를 다루었다. 基準모델과 未知시스템의 入·出力端에 狀態變數필터를 도입하므로서, 可用信號들로 구성된 아주 간단한 適應시스템을 구성할 수 있다. 未知시스템의 相對次數가 1 또는 2 이상인 경우의 設計法은 多數 발표되었으나, 構造가 매우 복잡하거나 設計理論이 일반화하지 못하였다. 본 論文에서는 相對次數가 2이상인 경우에 간단한 線型필터를 도입하므로서 適應構造를 간단히 구성할 수 있음을 證明하였다.

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