• Title/Summary/Keyword: coprime

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Coprime factor reduction of plant in $H{\infty}$ mixed sensitivity problem ($H{\infty}$ 혼합감도문제에서 플랜트의 소인수요소줄임)

  • 음태호;오도창;박홍배;김수중
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.2
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    • pp.20-27
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    • 1996
  • In this paper, we propose a coprime factor model reduction method to get a reduced order controller in $H^{\infty}$ mixed sensitivity problem with frequency weighting functions. for this purpose, the given $H^{\infty}$ mixed sensitivity problem is transformed into robust stabilization problem with coprime factor uncertainty of given plant. This method is to define frequency weighted coprime factors of plant in CSD (chain scattering description) form and reduce the coprime factors using weighted balanced truncation. then a controller is designed to the reduced order coprime factors using J-lossless coprime factorization method. Using this approach, the robust stability condition is derived and good performance is preserved in closed loop system with the given plant and the reduced order controller. Also the order of reduced controller for guaranteeing the robust stability can be determined before designing the reduced controller. The proposed method behaves well in both stable and unstable plant.

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Coprime factor reduction of plant in $H{\infty}$ mixed sensitivity problem

  • Um, Tae-Ho;Oh, Do-Chang;Park, Hong-Bea;Kim, Soo-Joong
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.340-343
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    • 1995
  • In this paper, we get a reduced order controller in $H^{\infty}$ mixed sensitivity problem with weighting functions. For this purpose, we define frequency weighted coprime factor of plant in $H^{\infty}$ mixed sensitivity problem and reduce the coprime factor using the frequency weighted balanced truncation technique. The we design the controller for plant with reduced order coprime factor using J-lossless coprime factorization technique. Using this approach, we can derive the robust stability condition and achieve good performance preservation in the closed loop system with reduced order controller. And it behaves well in both stable plant and unstable plant.t.

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An Analysis on Worst-case State Estimation in Standard H$\infty$ State-Space Solution

  • Choi, Youngjin;Chung, Wan-Kyun;Youm, Youngil
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.56-59
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    • 1996
  • Worst-case state estimation will be proposed in this paper. By using the worst-case disturbance and worst-case state estimation, we can obtain right/left constrained coprime factors. If constrained coprime factors are used in designing a controller, the infinity-norm of closed-loop transfer matrix can be smaller than any constant .gamma.(> .gamma.$_{opt}$) without matrix dilation optimization. The derivation of left/right constrained coprime factors is achieved by doubly coprime factorization for the plant constrained by the infinity norm. And the parameterization of stabilizing controllers gives us easily understanding for H$_{\infty}$ control theory.ry.

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Blind signal separation for coprime planar arrays: An improved coupled trilinear decomposition method

  • Zhongyuan Que;Xiaofei Zhang;Benzhou Jin
    • ETRI Journal
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    • v.45 no.1
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    • pp.138-149
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    • 2023
  • In this study, the problem of blind signal separation for coprime planar arrays is investigated. For coprime planar arrays comprising two uniform rectangular subarrays, we link the signal separation to the tensor-based model called coupled canonical polyadic decomposition (CPD) and propose an improved coupled trilinear decomposition approach. The output data of coprime planar arrays are modeled as a coupled tensor set that can be further interpreted as a coupled CPD model, allowing a signal separation to be achieved using coupled trilinear alternating least squares (TALS). Furthermore, in the procedure of the coupled TALS, a Vandermonde structure enforcing approach is explicitly applied, which is shown to ensure fast convergence. The results of Monto Carlo simulations show that our proposed algorithm has the same separation accuracy as the basic coupled TALS but with a faster convergence speed.

Coprime Factor Reduction of Parameter Varying Controller

  • Saragih, Roberd;Widowati, Widowati
    • International Journal of Control, Automation, and Systems
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    • v.6 no.6
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    • pp.836-844
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    • 2008
  • This paper presents an approach to order reduction of linear parameter varying controller for polytopic model. Feasible solutions which satisfy relevant linear matrix inequalities for constructing full-order parameter varying controller evaluated at each polytopic vertices are first found. Next, sufficient conditions are derived for the existence of a right coprime factorization of parameter varying controller. Furthermore, a singular perturbation approximation for time invariant systems is generalized to reduce full-order parameter varying controller via parameter varying right coprime factorization. This generalization is based on solutions of the parameter varying Lyapunov inequalities. The closed loop performance caused by using the reduced order controller is developed. To examine the performance of the reduced-order parameter varying controller, the proposed method is applied to reduce vibration of flexible structures having the transverse-torsional coupled vibration modes.

Reduced order controller using J-lossless coprime factorization and balanced transformation (J-lossless 소인수분해와 균형화된 변환을 이용한 제어기 차수줄임)

  • 오도창;정은태;엄태호;박홍배
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.1018-1023
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    • 1992
  • In this paper we proposed the systematic method of reducing the order of controller with robustness. State space formulae for all controllers is found by solving two coupled J-lossless coprime factorizations and model reduction problem. To reduce the order of controller, balanced truncation and Hankel approximation are used.

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A Fault Detection system Design for Uncertain Nonlinear Systems (불확실한 비선형시스템을 위한 고장검출 시스템 설계)

  • Yoo, Seog-Hwan;Choi, Byung-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.185-189
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    • 2007
  • This paper deals with a fault detection system design for nonlinear systems with uncertain time varying parameters modelled as a T-S fuzzy system. A coprime factorization for T-S fuzzy systems is defined and a residual generator is designed using a left coprime factor. A fault detection criteria derived from the residual generator is also suggested. In order to demonstrate the efficacy of the suggested method, the fault defection method is applied to an inverted pendulum system and computer simulations are performed.

A Fractional Model Reduction for T-S Fuzzy Systems with State Delay

  • Yoo Seog-Hwan;Choi Byung-Jae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.3
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    • pp.184-189
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    • 2006
  • This paper deals with a fractional model reduction for T-S fuzzy systems with time varying delayed states. A contractive coprime factorization of time delayed T-S fuzzy systems is defined and obtained by solving linear matrix inequalities. Using generalized controllability and observability gramians of the contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is performed.

A Fractional Model Reduction for Linear Systems with State Delay (상태변수 시간지연을 갖는 선형시스템의 분수 모델 축소)

  • Yoo, Seog-Hwan
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.41 no.2
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    • pp.29-36
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    • 2004
  • This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.