Discrete-continuous model conversion

Shieh, Leang-San; Wang, H.; Yates, R. E.

doi:10.1016/0307-904x(80)90177-8

Cited by 54 publications

(32 citation statements)

References 6 publications

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“…For a more detailed discussion of the above relationships refer to [9][10][11] . This equivalency provides the basis for a system identification algorithm 6 , which requires frequency response data on a set of M+1 equispaced discrete frequencies between 0 and .…”

Section: E System Identificationmentioning

confidence: 99%

Linear Frequency Domain Reduced Order Modelling of Aerofoil Gust Response

Bagheri¹,

Jones²,

Gaitonde³

2016

46th AIAA Fluid Dynamics Conference

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A method for constructing reduced order models of an aerofoil subject to gusts is presented. The method is based on subspace system identification in the frequency domain in order to obtain a model which retains the dynamic information of the original system, while having a comparatively smaller dimension. The gust is prescribed through the domain using the split velocity method to obtain the system frequency response. This is used to find the state matrices of the reduced system. By prescribing a series of 1-cosine gusts, it is shown that the reduced system obtained agrees well with the original system.

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Section: E System Identificationmentioning

confidence: 99%

Linear Frequency Domain Reduced Order Modelling of Aerofoil Gust Response

Bagheri¹,

Jones²,

Gaitonde³

2016

46th AIAA Fluid Dynamics Conference

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“…In his method, a logarithmic matrix function is converted to a logarithmic scalar function via a model transformation such that the approximate continuous model can be formulated from the discrete model. On the other hand, Shieh et al [2][3][4] have converted continuous-time state equations to equivalent discrete-time models via a block-pulse function method [3] and a geometric-series method [2]. However, these literatures by adopting Taylor series might get an approximate continuous to discrete model conversion, when the system has a singular system matrix.…”

Section: Introductionmentioning

confidence: 95%

Continuous to discrete model conversion for the system with a singular system matrix based on matrix sign function

Tsai

Huang

Guo

et al. 2011

Applied Mathematical Modelling

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a b s t r a c tThe analytic continuous to discrete model conversion for the system with a singular system matrix based on the computationally fast and numerically stable sign function is firstly presented in this note. The proposed methodology yields a more accurate model conversion than existing approximate methods. An illustrative example is presented to show the accuracy of the proposed methodology.

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“…Calculation of the Jacobian matrices and discrete-continuous model conversion are standard procedures [9] [10]. Since at the steady state, the voltages stay at desired values and the control action is…”

Section: A Power System Dynamicsmentioning

confidence: 99%

Nobody but you: MAC scheduling for voltage regulation in smart grid

Mao

2012

2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm)

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The increasing availability of distributed energy resources (DERs) and sensors in smart grid, as well as overlaying communication network, provides substantial potential benefits for improving the power system's reliability. In this paper, the problem of sensor selection is studied for the MAC layer design of wireless sensor networks for regulating the voltages in smart grid. The framework of hybrid dynamical system is proposed, using Kalman filter for voltage state estimation, and linear-quadratic regulator (LQR) feedback controller for voltage adjustment. The approach to obtain the optimal sensor selection sequence is studied. A sub-optimal sequence is obtained by applying the sliding window algorithm. Simulation results show that the proposed sensor selection strategy achieves a 40% performance gain over the baseline algorithm of the round-robin sensor polling.

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Discrete-continuous model conversion

Cited by 54 publications

References 6 publications

Linear Frequency Domain Reduced Order Modelling of Aerofoil Gust Response

Linear Frequency Domain Reduced Order Modelling of Aerofoil Gust Response

Continuous to discrete model conversion for the system with a singular system matrix based on matrix sign function

Nobody but you: MAC scheduling for voltage regulation in smart grid

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