• Title/Summary/Keyword: Minimum Phase Condition

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Application of Minimum Phase Condition to Acoustic Impedance Measurement (최소 위상 조건을 적용한 음향 임피던스 측정)

  • Lim, Byoung-Duk;Heo, Jun-Hyeok
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.855-860
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    • 2005
  • For the accurate measurement of acoustic properties of a surface, efforts have been made to reduce errors caused by external disturbance. If the reflection coefficient is considered as a transfer function between reflected wave and incident wave, causality is required between them and the reflection coefficient should be of minimum phase. In this thesis, the minimum phase condition is applied to measure correct reflection coefficient. The reflection coefficient is approximated as a rational function in the Z domain by minimizing the sum square error. Then the minimum phase reflection coefficient is reconstructed using the distribution of poles and zeros of the reflection coefficient model. The incident wave, the reflected wave and the impulse response function of causality are recalculated from the minimum phase reflection coefficient for further applications.

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Application of Minimum Phase Condition to the Acoustic Reflection Coefficient Measurement (최소 위상 조건을 적용한 음향 반사계수 측정)

  • Heo, Jun-Hyeok;Kim, Deok-Ki;Lim, Byoung-Duk
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.15 no.10 s.103
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    • pp.1131-1136
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    • 2005
  • For the accurate measurement of acoustic properties of a surface, efforts have been made to reduce errors caused by external disturbance. If the reflection coefficient is considered as a transfer function between reflected wane and incident wave, the causality is required between them and the reflection coefficient should be of minimum phase. In this thesis, the minimum phase condition is applied to measure correct reflection coefficient. The reflection coefficient is approximated as a rational function In the Z domain by minimizing the sum square error. Then the minimum phase reflection coefficient is reconstructed using the distribution of poles and zeros of the reflection coefficient model.

A FILTERING CONDITION AND STOCHASTIC ADAPTIVE CONTROL USING NEURAL NETWORK FOR MINIMUM-PHASE STOCHASTIC NONLINEAR SYSTEM (최소위상 확률 비선형 시스템을 위한 필터링 조건과 신경회로망을 사용한 적응제어)

  • Seok, Jin-Wuk
    • Proceedings of the KIEE Conference
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    • 2001.11c
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    • pp.18-21
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    • 2001
  • In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network me provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. In the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shoo's that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller.

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ADAPTIVE CONTROL USING NEURAL NETWORK FOR MINIMUM-PHASE STOCHASTIC NONLINEAR SYSTEM

  • Seok, Jinwuk
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.18-18
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    • 2000
  • In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network are provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shows that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller

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Analysis and Design Using LMI Condition for C (sI-A)^{-1} to Be Minimum Phase (C(sI-A)-1B가 최소위상이 될 LMI 조건을 이용한 해석과 설계)

  • Lee Jae-Kwan;Choi Han Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.11
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    • pp.895-900
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    • 2005
  • We derive a linear matrix inequality(LMI) condition guaranteeing that any invariant zeros of a triple (A, B, C) lie in the open left half plane of the complex plane, i.e. $C(sI-A)^{-1}B$ is minimum phase. The LMI condition is equivalent to a certain constrained Lyapunov matrix equation which can be found in many results relating to stability analysis or control design. We show that the LMI condition can be used to simplify various control engineering problems such as a dynamic output feedback control problem, a variable structure static output feedback control problem, and a nonlinear system observer design problem. Finally, we give some numerical examples.

Output Feedback Stabilization of Non-Minimum Phase Nonlinear Systems

  • Jo, Nam-H.;Son, Young-I.;Shim, Hyung-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.60.1-60
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    • 2002
  • . an output feedback stabilizing controller for non-minimum phase nonlinear systems . Assumption 1 : the Jacobi linearization of the given nonlinear linear system is controllable . Assumption 2: an appropriate transformation which transforms the zero dynamics into a special form . Assumption 3: the system satisfies the observability rank condition . Augmentation of systems by augmented by a chain of integrators

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A Study on the Convergence Condition of ILC for Linear Discrete Time Nonminimum Phase Systems (이산 선형 비최소위상 시스템을 위한 반복 학습 제어의 수렴조건에 대한 연구)

  • Bae, Sung-Han;Ahn, Hyun-Sik;Jeong, Gu-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.1
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    • pp.117-120
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    • 2008
  • This paper investigates the convergence condition of ADILC(iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

On the Convergence of ILC for Linear Discrete Time Nonminimum Phase Systems (이산 선형 시스템에 대한 반복 학습 제어의 수렴성에 대한 연구)

  • Jeong, Gu-Min;Ahn, Hyun-Sik
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.225-227
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    • 2006
  • This note investigates the convergence condition of ADILC (iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

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Minimum-Entropy-Based Autofocus Method for Real SAR Images (실제 SAR 영상에서의 최소 엔트로피 기반의 자동 초점 기법 연구)

  • Hwang, Jeonghun;Shin, Hyun-Ik;Kim, Whan-Woo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.5
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    • pp.366-374
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    • 2018
  • In cases of airborne equipped with SAR, because the occurrence of motion is inevitable, it is necessary to apply autofocus techniques to SAR images to improve the image performance degradations caused by residual errors. Herein, a robust autofocus algorithm based on the minimum entropy criteria is proposed for the real SAR data in the spotlight mode. The convergence condition of the phase error estimation is checked at every iteration and if it is violated, the size of the phase error estimation is adjusted to the convergence condition. The real SAR raw data is used to demonstrate the excellent performance of the proposed algorithm.

Improved Phase and Harmonic Detection Scheme using Fast Fourier Transform with Minimum Sampling Data under Distorted Grid Voltage (최소 샘플링의 고속푸리에 변환을 이용한 비정상 계통의 향상된 위상추종 및 고조파 검출 기법)

  • Kim, Hyun-Sou;Kim, Kyeong-Hwa
    • The Transactions of the Korean Institute of Power Electronics
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    • v.20 no.1
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    • pp.72-80
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    • 2015
  • In distributed generation systems, a grid-connected inverter should operate with synchronization to grid voltage. Considering that synchronization requires the phase angle of grid voltage, a phase locked loop (PLL) scheme is often used. The synchronous reference frame phase locked loop (SRF-PLL) is generally known to provide reasonable performance under ideal grid voltage. However, this scheme indicates performance degradation under the harmonic distorted or unbalanced grid voltage condition. To overcome this limitation, this paper proposes a phase and harmonic detection method of grid voltage using fast Fourier transform (FFT). To reduce the calculation time of FFT algorithm, minimum sampling data is taken from the voltage measurement to determine the phase angle and the magnitude of harmonic components. An experimental test setup for a grid-connected inverter system has been constructed. By comparative simulations and experiments under various abnormal grid voltage conditions, the proposed scheme has been proven to effectively track the phase angle of the grid voltage.